diff --git a/Puberty_CFA_sMRI.Rmd b/Puberty_CFA_sMRI.Rmd index be7828f..efdf7ee 100644 --- a/Puberty_CFA_sMRI.Rmd +++ b/Puberty_CFA_sMRI.Rmd @@ -1408,116 +1408,6 @@ write.csv(pub_corr$n, "Z:/TAG/projects/W1_puberty_modelling/puberty_sMRI/pubsmri write.csv(pub_corr$P, "Z:/TAG/projects/W1_puberty_modelling/puberty_sMRI/pubsmri_p.csv") ``` -```{r saliva correlations} - -# One reviewer suggested looking at how much each sample (day) correlated within hormones, and whether this changed by pubertal stage -# Below, we fit data to additional SEM models separately by hormone to assess how well they fit onto a latent factor; -# the loadings tell us how each sample (day of saliva collection) fits. -# Additional models per hormone were also fit with the sample separated into high and low Tanner stage. - -Timing_allways_w1_forsMRI <- read_csv("Z:/TAG/projects/W1_W2_pubertal_timing/Timing_allways_w1_forsMRI.csv") -pubvars2 <- c("SID","pdsstage") -pdsstage <- Timing_allways_w1_forsMRI[pubvars2] -data_pds <- merge( - x = data, - y = pdsstage, - by = "SID", - all = FALSE) - -median(data_pds$pdsstage, na.rm = TRUE) -tanner_high <- data[which(data_pds$pdsstage >= 3), ] -tanner_low <- data[which(data_pds$pdsstage < 3), ] - -#DHEA -DHEA_noSR <- " - -#Saliva Day -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 - -" - -# Fit DHEA everyone -fit_DHEA_noSR <- cfa(DHEA_noSR, data = data, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_DHEA_noSR, fit.measures = T, standardized = T) -fitmea_fit_DHEA_noSR <- fitmeasures(fit_DHEA_noSR, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -# Fit DHEA high tanner -fit_DHEA_tannerhigh <- cfa(DHEA_noSR, data = tanner_high, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_DHEA_tannerhigh, fit.measures = T, standardized = T) -fitmea_fit_DHEA_tannerhigh <- fitmeasures(fit_DHEA_tannerhigh, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -# Fit DHEA low tanner -fit_DHEA_tannerlow <- cfa(DHEA_noSR, data = tanner_low, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_DHEA_tannerlow, fit.measures = T, standardized = T) -fitmea_fit_DHEA_tannerlow <- fitmeasures(fit_DHEA_tannerlow, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -#Testosterone -T_noSR <- " - -#Saliva Day -sal_test =~ test1 + test2 + test3 + test4 - -" - -# Fit T everyone -fit_T_noSR <- cfa(T_noSR, data = data, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_T_noSR, fit.measures = T, standardized = T) -fitmea_fit_T_noSR <- fitmeasures(fit_T_noSR, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -# Fit T high tanner -fit_T_tannerhigh <- cfa(T_noSR, data = tanner_high, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_T_tannerhigh, fit.measures = T, standardized = T) -fitmea_fit_T_tannerhigh <- fitmeasures(fit_T_tannerhigh, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -# Fit T low tanner -fit_T_tannerlow <- cfa(T_noSR, data = tanner_low, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_T_tannerlow, fit.measures = T, standardized = T) -fitmea_fit_T_tannerlow <- fitmeasures(fit_T_tannerlow, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -#E2 -E2_noSR <- " - -#Saliva Day -sal_estr =~ estr1 + estr2 + estr3 + estr4 - -" - -# Fit E2 everyone -fit_E2_noSR <- cfa(E2_noSR, data = data, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_E2_noSR, fit.measures = T, standardized = T) -fitmea_fit_E2_noSR <- fitmeasures(fit_E2_noSR, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -# Fit E2 high tanner -fit_E2_tannerhigh <- cfa(E2_noSR, data = tanner_high, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_E2_tannerhigh, fit.measures = T, standardized = T) -fitmea_fit_E2_tannerhigh <- fitmeasures(fit_E2_tannerhigh, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -# Fit E2 low tanner -fit_E2_tannerlow <- cfa(E2_noSR, data = tanner_low, estimator = "ML", - missing = "ML", verbose = T) -summary(fit_E2_tannerlow, fit.measures = T, standardized = T) -fitmea_fit_E2_tannerlow <- fitmeasures(fit_E2_tannerlow, - fit.measures = c("cfi","ecvi","mfi", "chisq", "pvalue", "rmsea", "srmr")) - -``` - - ```{r sMRI} ########## sMRI POSTHOC ANALYSES ########## # Do what we did for age above but for cortical thickness values. @@ -1763,7 +1653,46 @@ lh_bankssts_fac =~ lh_bankssts_thickness #age factor agefac =~ age " +# Fit models +fit_fm2v3_lh_bankssts_cor <- cfa(fm2v3_lh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm2v3_lh_bankssts_corage <- cfa(fm2v3_lh_bankssts_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_bankssts_cor <- cfa(fm1v3_lh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_bankssts_corage <- cfa(fm1v3_lh_bankssts_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_bankssts_cor <- cfa(sr1_lh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_bankssts_corage <- cfa(sr1_lh_bankssts_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_bankssts_cor <- cfa(sr2_lh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_bankssts_corage <- cfa(sr2_lh_bankssts_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_bankssts_cor <- cfa(hm1_lh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_bankssts_corage <- cfa(hm1_lh_bankssts_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_bankssts_cor <- cfa(hm2_lh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_bankssts_corage <- cfa(hm2_lh_bankssts_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) + +# Summary Stats for models +summary(fit_fm2v3_lh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_fm2v3_lh_bankssts_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_bankssts_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_bankssts_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_bankssts_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_bankssts_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_bankssts_corage, fit.measures = T, standardized = T) ####### lh_caudalanteriorcingulate_thickness ####### @@ -1992,6 +1921,54 @@ lh_caudalanteriorcingulate_fac =~ lh_caudalanteriorcingulate_thickness agefac =~ age " +brainvars <- c("lh_bankssts_thickness", "lh_caudalanteriorcingulate_thickness") + +for {i in brainvars} + +paste("fit_fm2v3_",i, "_cor") <- cfa(paste("fm2v3_",li,"_cor", data = data, estimator = "ML", + missing = "ML", verbose = T) + +# Fit models +fit_fm2v3_lh_caudalanteriorcingulate_cor <- cfa(fm2v3_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_caudalanteriorcingulate_cor <- cfa(fm1v3_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_caudalanteriorcingulate_cor <- cfa(sr1_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_caudalanteriorcingulate_cor <- cfa(sr2_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_caudalanteriorcingulate_cor <- cfa(hm1_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_caudalanteriorcingulate_cor <- cfa(hm2_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) + +fit_fm2v3_lh_caudalanteriorcingulate_corage <- cfa(fm2v3_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_caudalanteriorcingulate_corage <- cfa(fm1v3_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_caudalanteriorcingulate_corage <- cfa(sr1_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_caudalanteriorcingulate_corage <- cfa(sr2_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_caudalanteriorcingulate_corage <- cfa(hm1_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_caudalanteriorcingulate_corage <- cfa(hm2_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +# Summary Stats for models +summary(fit_fm2v3_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) + +summary(fit_fm2v3_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) + ####### lh_caudalmiddlefrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness @@ -2220,6 +2197,47 @@ lh_caudalmiddlefrontal_fac =~ lh_caudalmiddlefrontal_thickness #age factor agefac =~ age " +# Fit models +fit_fm2v3_lh_caudalmiddlefrontal_cor <- cfa(fm2v3_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_caudalmiddlefrontal_cor <- cfa(fm1v3_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_caudalmiddlefrontal_cor <- cfa(sr1_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_caudalmiddlefrontal_cor <- cfa(sr2_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_caudalmiddlefrontal_cor <- cfa(hm1_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_caudalmiddlefrontal_cor <- cfa(hm2_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) + +fit_fm2v3_lh_caudalmiddlefrontal_corage <- cfa(fm2v3_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_caudalmiddlefrontal_corage <- cfa(fm1v3_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_caudalmiddlefrontal_corage <- cfa(sr1_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_caudalmiddlefrontal_corage <- cfa(sr2_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_caudalmiddlefrontal_corage <- cfa(hm1_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_caudalmiddlefrontal_corage <- cfa(hm2_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) + +# Summary Stats for models +summary(fit_fm2v3_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) + +summary(fit_fm2v3_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) ####### lh_cuneus_thickness ####### @@ -2444,6 +2462,48 @@ lh_cuneus_fac =~ lh_cuneus_thickness agefac =~ age " +# Fit models +fit_fm2v3_lh_cuneus_cor <- cfa(fm2v3_lh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_cuneus_cor <- cfa(fm1v3_lh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_cuneus_cor <- cfa(sr1_lh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_cuneus_cor <- cfa(sr2_lh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_cuneus_cor <- cfa(hm1_lh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_cuneus_cor <- cfa(hm2_lh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) + +fit_fm2v3_lh_cuneus_corage <- cfa(fm2v3_lh_cuneus_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_cuneus_corage <- cfa(fm1v3_lh_cuneus_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_cuneus_corage <- cfa(sr1_lh_cuneus_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_cuneus_corage <- cfa(sr2_lh_cuneus_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_cuneus_corage <- cfa(hm1_lh_cuneus_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_cuneus_corage <- cfa(hm2_lh_cuneus_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) + + +# Summary Stats for models +summary(fit_fm2v3_lh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_cuneus_cor, fit.measures = T, standardized = T) + +summary(fit_fm2v3_lh_cuneus_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_cuneus_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_cuneus_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_cuneus_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_cuneus_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_cuneus_corage, fit.measures = T, standardized = T) ####### lh_entorhinal_thickness ####### @@ -2668,6 +2728,47 @@ lh_entorhinal_fac =~ lh_entorhinal_thickness #age factor agefac =~ age " +# Fit models +fit_fm2v3_lh_entorhinal_cor <- cfa(fm2v3_lh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_entorhinal_cor <- cfa(fm1v3_lh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_entorhinal_cor <- cfa(sr1_lh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_entorhinal_cor <- cfa(sr2_lh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_entorhinal_cor <- cfa(hm1_lh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_entorhinal_cor <- cfa(hm2_lh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) + +fit_fm2v3_lh_entorhinal_corage <- cfa(fm2v3_lh_entorhinal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_entorhinal_corage <- cfa(fm1v3_lh_entorhinal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_entorhinal_corage <- cfa(sr1_lh_entorhinal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_entorhinal_corage <- cfa(sr2_lh_entorhinal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_entorhinal_corage <- cfa(hm1_lh_entorhinal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_entorhinal_corage <- cfa(hm2_lh_entorhinal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) + +# Summary Stats for models +summary(fit_fm2v3_lh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_entorhinal_cor, fit.measures = T, standardized = T) + +summary(fit_fm2v3_lh_entorhinal_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_entorhinal_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_entorhinal_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_entorhinal_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_entorhinal_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_entorhinal_corage, fit.measures = T, standardized = T) ####### lh_fusiform_thickness ####### @@ -2770,7 +2871,7 @@ estr4 ~~ test4 lh_fusiform_fac =~ lh_fusiform_thickness " -fm1v3_lh_fusiform_corage <- " +fm1v3_lh_fusiform_cor <- " #Latent Variables #Saliva - Level 1 @@ -2888,7 +2989,7 @@ adrenal =~ sal_dhea + sal_test lh_fusiform_fac =~ lh_fusiform_thickness " -hm2_lh_fusiform_corage <- " +hm2_lh_fusiform_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -2903,8 +3004,49 @@ lh_fusiform_fac =~ lh_fusiform_thickness #age factor agefac =~ age " - - +# Fit models +fit_fm2v3_lh_fusiform_cor <- cfa(fm2v3_lh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_fusiform_cor <- cfa(fm1v3_lh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_fusiform_cor <- cfa(sr1_lh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_fusiform_cor <- cfa(sr2_lh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_fusiform_cor <- cfa(hm1_lh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_fusiform_cor <- cfa(hm2_lh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T,) + +fit_fm2v3_lh_fusiform_corage <- cfa(fm2v3_lh_fusiform_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_fusiform_corage <- cfa(fm1v3_lh_fusiform_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_fusiform_corage <- cfa(sr1_lh_fusiform_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_fusiform_corage <- cfa(sr2_lh_fusiform_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_fusiform_corage <- cfa(hm1_lh_fusiform_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_fusiform_corage <- cfa(hm2_lh_fusiform_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T,) + + +# Summary Stats for models +summary(fit_fm2v3_lh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_fusiform_cor, fit.measures = T, standardized = T) + +summary(fit_fm2v3_lh_fusiform_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_fusiform_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_fusiform_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_fusiform_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_fusiform_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_fusiform_corage, fit.measures = T, standardized = T) + ####### left inferior parietal ####### # Now build the first one, ADR and GON correlate with thickness @@ -3139,43 +3281,54 @@ lh_inferiorparietal_fac =~ lh_inferiorparietal_thickness #age factor agefac =~ age " +# Fit models +fit_fm2v3_lh_inferiorparietal_cor <- cfa(fm2v3_lh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_inferiorparietal_cor <- cfa(fm1v3_lh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_inferiorparietal_cor <- cfa(sr1_lh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_inferiorparietal_cor <- cfa(sr2_lh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_inferiorparietal_cor <- cfa(hm1_lh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_inferiorparietal_cor <- cfa(hm2_lh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) -####### lh_inferiortemporal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_inferiortemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm2v3_lh_inferiorparietal_corage <- cfa(fm2v3_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_lh_inferiorparietal_corage <- cfa(fm1v3_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_lh_inferiorparietal_corage <- cfa(sr1_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_lh_inferiorparietal_corage <- cfa(sr2_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_lh_inferiorparietal_corage <- cfa(hm1_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_lh_inferiorparietal_corage <- cfa(hm2_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", + missing = "ML", verbose = T) -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +# Summary Stats for models +summary(fit_fm2v3_lh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_inferiorparietal_cor, fit.measures = T, standardized = T) -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 +summary(fit_fm2v3_lh_inferiorparietal_corage, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_inferiorparietal_corage, fit.measures = T, standardized = T) +summary(fit_sr1_lh_inferiorparietal_corage, fit.measures = T, standardized = T) +summary(fit_sr2_lh_inferiorparietal_corage, fit.measures = T, standardized = T) +summary(fit_hm1_lh_inferiorparietal_corage, fit.measures = T, standardized = T) +summary(fit_hm2_lh_inferiorparietal_corage, fit.measures = T, standardized = T) -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness -" +####### lh_inferiortemporal_thickness ####### -fm2v3_lh_inferiortemporal_corage <- " +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_inferiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -3204,9 +3357,6 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness - -#age factor -agefac =~ age " # Check the thickness correlation with the one factor PUB latent variable, too @@ -3240,41 +3390,6 @@ estr4 ~~ test4 #thickness factor lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness " - -fm1v3_lh_inferiortemporal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness - -#age factor -agefac =~ age -" - # Do the same for self-report models only sr1_lh_inferiortemporal_cor <- " #Latent Neuroendocrine Systems @@ -3284,17 +3399,6 @@ puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness " -sr1_lh_inferiortemporal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness - -#age factor -agefac =~ age -" - sr2_lh_inferiortemporal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 @@ -3304,18 +3408,6 @@ gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness " -sr2_lh_inferiortemporal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness - -#age factor -agefac =~ age -" - # And for hormone models only hm1_lh_inferiortemporal_cor <- " #Saliva - Level 1 @@ -3330,22 +3422,6 @@ puberty =~ sal_dhea + sal_estr + sal_test lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness " -hm1_lh_inferiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness - -#age factor -agefac =~ age -" - hm2_lh_inferiortemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 @@ -3358,24 +3434,39 @@ adrenal =~ sal_dhea + sal_test #thickness factor lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness " +# Fit models +fit_fm2v3_lh_inferiortemporal_cor <- cfa(fm2v3_lh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_inferiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_inferiortemporal_cor <- cfa(fm1v3_lh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_inferiortemporal_cor <- cfa(sr1_lh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_inferiortemporal_fac =~ lh_inferiortemporal_thickness +fit_sr2_lh_inferiortemporal_cor <- cfa(sr2_lh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_inferiortemporal_cor <- cfa(hm1_lh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_inferiortemporal_cor <- cfa(hm2_lh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +# Summary Stats for models +summary(fit_fm2v3_lh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_inferiortemporal_cor, fit.measures = T, standardized = T) + ####### lh_isthmuscingulate_thickness ####### # Now build the first one, ADR and GON correlate with thickness @@ -3411,40 +3502,6 @@ estr4 ~~ test4 lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness " -fm2v3_lh_isthmuscingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness - -#age factor -agefac =~ age -" - # Check the thickness correlation with the one factor PUB latent variable, too fm1v3_lh_isthmuscingulate_cor <- " #Latent Variables @@ -3476,41 +3533,6 @@ estr4 ~~ test4 #thickness factor lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness " - -fm1v3_lh_isthmuscingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness - -#age factor -agefac =~ age -" - # Do the same for self-report models only sr1_lh_isthmuscingulate_cor <- " #Latent Neuroendocrine Systems @@ -3520,17 +3542,6 @@ puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness " -sr1_lh_isthmuscingulate_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness - -#age factor -agefac =~ age -" - sr2_lh_isthmuscingulate_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 @@ -3540,18 +3551,6 @@ gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness " -sr2_lh_isthmuscingulate_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness - -#age factor -agefac =~ age -" - # And for hormone models only hm1_lh_isthmuscingulate_cor <- " #Saliva - Level 1 @@ -3566,22 +3565,6 @@ puberty =~ sal_dhea + sal_estr + sal_test lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness " -hm1_lh_isthmuscingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness - -#age factor -agefac =~ age -" - hm2_lh_isthmuscingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 @@ -3594,23 +3577,38 @@ adrenal =~ sal_dhea + sal_test #thickness factor lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness " +# Fit models +fit_fm2v3_lh_isthmuscingulate_cor <- cfa(fm2v3_lh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_isthmuscingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_isthmuscingulate_cor <- cfa(fm1v3_lh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_isthmuscingulate_cor <- cfa(sr1_lh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_isthmuscingulate_fac =~ lh_isthmuscingulate_thickness +fit_sr2_lh_isthmuscingulate_cor <- cfa(sr2_lh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_isthmuscingulate_cor <- cfa(hm1_lh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_isthmuscingulate_cor <- cfa(hm2_lh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) ####### lh_lateraloccipital_thickness ####### @@ -3647,40 +3645,6 @@ estr4 ~~ test4 lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness " -fm2v3_lh_lateraloccipital_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness - -#age factor -agefac =~ age -" - # Check the thickness correlation with the one factor PUB latent variable, too fm1v3_lh_lateraloccipital_cor <- " #Latent Variables @@ -3712,40 +3676,6 @@ estr4 ~~ test4 #thickness factor lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness " - -fm1v3_lh_lateraloccipital_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness - -#age factor -agefac =~ age -" # Do the same for self-report models only sr1_lh_lateraloccipital_cor <- " #Latent Neuroendocrine Systems @@ -3755,17 +3685,6 @@ puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness " -sr1_lh_lateraloccipital_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness - -#age factor -agefac =~ age -" - sr2_lh_lateraloccipital_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 @@ -3775,18 +3694,6 @@ gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness " -sr2_lh_lateraloccipital_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness - -#age factor -agefac =~ age -" - # And for hormone models only hm1_lh_lateraloccipital_cor <- " #Saliva - Level 1 @@ -3801,22 +3708,6 @@ puberty =~ sal_dhea + sal_estr + sal_test lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness " -hm1_lh_lateraloccipital_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness - -#age factor -agefac =~ age -" - hm2_lh_lateraloccipital_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 @@ -3829,22 +3720,38 @@ adrenal =~ sal_dhea + sal_test #thickness factor lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness " +# Fit models +fit_fm2v3_lh_lateraloccipital_cor <- cfa(fm2v3_lh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_lateraloccipital_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_lateraloccipital_cor <- cfa(fm1v3_lh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_lateraloccipital_cor <- cfa(sr1_lh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_lateraloccipital_fac =~ lh_lateraloccipital_thickness +fit_sr2_lh_lateraloccipital_cor <- cfa(sr2_lh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_lateraloccipital_cor <- cfa(hm1_lh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_lateraloccipital_cor <- cfa(hm2_lh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_lateraloccipital_cor, fit.measures = T, standardized = T) ####### lh_lateralorbitofrontal_thickness ####### @@ -3881,7 +3788,8 @@ estr4 ~~ test4 lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness " -fm2v3_lh_lateralorbitofrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_lateralorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -3890,12 +3798,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -3907,16 +3816,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) +#thickness factor lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +" +# Do the same for self-report models only +sr1_lh_lateralorbitofrontal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_lateralorbitofrontal_cor <- " +sr2_lh_lateralorbitofrontal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +" + +# And for hormone models only +hm1_lh_lateralorbitofrontal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +" + +hm2_lh_lateralorbitofrontal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +" +# Fit models +fit_fm2v3_lh_lateralorbitofrontal_cor <- cfa(fm2v3_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_lateralorbitofrontal_cor <- cfa(fm1v3_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_lateralorbitofrontal_cor <- cfa(sr1_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_lateralorbitofrontal_cor <- cfa(sr2_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_lateralorbitofrontal_cor <- cfa(hm1_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_lateralorbitofrontal_cor <- cfa(hm2_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) + +####### lh_lingual_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_lingual_cor <- " #Latent Variables #Saliva - Level 1 @@ -3925,13 +3909,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -3943,11 +3926,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_lingual_fac =~ lh_lingual_thickness " -fm1v3_lh_lateralorbitofrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_lingual_cor <- " #Latent Variables #Saliva - Level 1 @@ -3975,55 +3960,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age +lh_lingual_fac =~ lh_lingual_thickness " - # Do the same for self-report models only -sr1_lh_lateralorbitofrontal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness -" - -sr1_lh_lateralorbitofrontal_corage <- " +sr1_lh_lingual_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age -" - -sr2_lh_lateralorbitofrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +lh_lingual_fac =~ lh_lingual_thickness " -sr2_lh_lateralorbitofrontal_corage <- " +sr2_lh_lingual_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age +lh_lingual_fac =~ lh_lingual_thickness " # And for hormone models only -hm1_lh_lateralorbitofrontal_cor <- " +hm1_lh_lingual_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4033,90 +3991,59 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness +lh_lingual_fac =~ lh_lingual_thickness " -hm1_lh_lateralorbitofrontal_corage <- " +hm2_lh_lingual_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +adrenal =~ sal_dhea + sal_test #thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age +lh_lingual_fac =~ lh_lingual_thickness " +# Fit models +fit_fm2v3_lh_lingual_cor <- cfa(fm2v3_lh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_lateralorbitofrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_fm1v3_lh_lingual_cor <- cfa(fm1v3_lh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness -" +fit_sr1_lh_lingual_cor <- cfa(sr1_lh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_lateralorbitofrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_lingual_cor <- cfa(sr2_lh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_lingual_cor <- cfa(hm1_lh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_lingual_cor <- cfa(hm2_lh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_lateralorbitofrontal_fac =~ lh_lateralorbitofrontal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_lingual_cor, fit.measures = T, standardized = T) -####### lh_lingual_thickness ####### +####### lh_medialorbitofrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_lingual_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_lingual_fac =~ lh_lingual_thickness -" - -fm2v3_lh_lingual_corage <- " +fm2v3_lh_medialorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -4144,14 +4071,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_lingual_fac =~ lh_lingual_thickness - -#age factor -agefac =~ age +lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_lingual_cor <- " +fm1v3_lh_medialorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -4179,99 +4103,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_lingual_fac =~ lh_lingual_thickness +lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +" +# Do the same for self-report models only +sr1_lh_medialorbitofrontal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#thickness factor +lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness " -fm1v3_lh_lingual_corage <- " -#Latent Variables +sr2_lh_medialorbitofrontal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +" -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_lh_lingual_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness -" - -sr1_lh_lingual_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness - -#age factor -agefac =~ age -" - -sr2_lh_lingual_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness -" - -sr2_lh_lingual_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_lh_lingual_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness -" - -hm1_lh_lingual_corage <- " +# And for hormone models only +hm1_lh_medialorbitofrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4281,13 +4134,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_lingual_fac =~ lh_lingual_thickness - -#age factor -agefac =~ age +lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness " -hm2_lh_lingual_cor <- " +hm2_lh_medialorbitofrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4297,31 +4147,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_lingual_fac =~ lh_lingual_thickness +lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness " +# Fit models +fit_fm2v3_lh_medialorbitofrontal_cor <- cfa(fm2v3_lh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_lingual_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_medialorbitofrontal_cor <- cfa(fm1v3_lh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_medialorbitofrontal_cor <- cfa(sr1_lh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_lingual_fac =~ lh_lingual_thickness +fit_sr2_lh_medialorbitofrontal_cor <- cfa(sr2_lh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_medialorbitofrontal_cor <- cfa(hm1_lh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_medialorbitofrontal_cor <- cfa(hm2_lh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -####### lh_medialorbitofrontal_thickness ####### +# Summary Stats for models +summary(fit_fm2v3_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) + +####### lh_middletemporal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_medialorbitofrontal_cor <- " +fm2v3_lh_middletemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -4349,10 +4214,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +lh_middletemporal_fac =~ lh_middletemporal_thickness " -fm2v3_lh_medialorbitofrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_middletemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -4361,12 +4227,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -4378,16 +4245,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +#thickness factor +lh_middletemporal_fac =~ lh_middletemporal_thickness +" +# Do the same for self-report models only +sr1_lh_middletemporal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_middletemporal_fac =~ lh_middletemporal_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_medialorbitofrontal_cor <- " +sr2_lh_middletemporal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_middletemporal_fac =~ lh_middletemporal_thickness +" + +# And for hormone models only +hm1_lh_middletemporal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +lh_middletemporal_fac =~ lh_middletemporal_thickness +" + +hm2_lh_middletemporal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_middletemporal_fac =~ lh_middletemporal_thickness +" +# Fit models +fit_fm2v3_lh_middletemporal_cor <- cfa(fm2v3_lh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_middletemporal_cor <- cfa(fm1v3_lh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_middletemporal_cor <- cfa(sr1_lh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_middletemporal_cor <- cfa(sr2_lh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_middletemporal_cor <- cfa(hm1_lh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_middletemporal_cor <- cfa(hm2_lh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_middletemporal_cor, fit.measures = T, standardized = T) + +####### lh_parahippocampal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_parahippocampal_cor <- " #Latent Variables #Saliva - Level 1 @@ -4396,13 +4338,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -4414,11 +4355,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_parahippocampal_fac =~ lh_parahippocampal_thickness " -fm1v3_lh_medialorbitofrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_parahippocampal_cor <- " #Latent Variables #Saliva - Level 1 @@ -4446,68 +4389,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness - -#age factor -agefac =~ age +lh_parahippocampal_fac =~ lh_parahippocampal_thickness " - # Do the same for self-report models only -sr1_lh_medialorbitofrontal_cor <- " +sr1_lh_parahippocampal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness -" - -sr1_lh_medialorbitofrontal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness - -#age factor -agefac =~ age -" - -sr2_lh_medialorbitofrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +lh_parahippocampal_fac =~ lh_parahippocampal_thickness " -sr2_lh_medialorbitofrontal_corage <- " +sr2_lh_parahippocampal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness - -#age factor -agefac =~ age +lh_parahippocampal_fac =~ lh_parahippocampal_thickness " # And for hormone models only -hm1_lh_medialorbitofrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness -" - -hm1_lh_medialorbitofrontal_corage <- " +hm1_lh_parahippocampal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4517,13 +4420,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness - -#age factor -agefac =~ age +lh_parahippocampal_fac =~ lh_parahippocampal_thickness " -hm2_lh_medialorbitofrontal_cor <- " +hm2_lh_parahippocampal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4533,62 +4433,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +lh_parahippocampal_fac =~ lh_parahippocampal_thickness " +# Fit models +fit_fm2v3_lh_parahippocampal_cor <- cfa(fm2v3_lh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_medialorbitofrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_parahippocampal_cor <- cfa(fm1v3_lh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_parahippocampal_cor <- cfa(sr1_lh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_medialorbitofrontal_fac =~ lh_medialorbitofrontal_thickness +fit_sr2_lh_parahippocampal_cor <- cfa(sr2_lh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_parahippocampal_cor <- cfa(hm1_lh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_parahippocampal_cor <- cfa(hm2_lh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -####### lh_middletemporal_thickness ####### +# Summary Stats for models +summary(fit_fm2v3_lh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_parahippocampal_cor, fit.measures = T, standardized = T) + +####### lh_paracentral_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_middletemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_middletemporal_fac =~ lh_middletemporal_thickness -" - -fm2v3_lh_middletemporal_corage <- " +fm2v3_lh_paracentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -4616,45 +4500,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_middletemporal_fac =~ lh_middletemporal_thickness - -#age factor -agefac =~ age +lh_paracentral_fac =~ lh_paracentral_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_middletemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness -" - -fm1v3_lh_middletemporal_corage <- " +fm1v3_lh_paracentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -4682,53 +4532,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness - -#age factor -agefac =~ age +lh_paracentral_fac =~ lh_paracentral_thickness " - # Do the same for self-report models only -sr1_lh_middletemporal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness -" -sr1_lh_middletemporal_corage <- " +sr1_lh_paracentral_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness - -#age factor -agefac =~ age +lh_paracentral_fac =~ lh_paracentral_thickness " -sr2_lh_middletemporal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness -" -sr2_lh_middletemporal_corage <- " +sr2_lh_paracentral_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness - -#age factor -agefac =~ age +lh_paracentral_fac =~ lh_paracentral_thickness " # And for hormone models only -hm1_lh_middletemporal_cor <- " +hm1_lh_paracentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4738,57 +4563,59 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness +lh_paracentral_fac =~ lh_paracentral_thickness " -hm1_lh_middletemporal_corage <- " + +hm2_lh_paracentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +adrenal =~ sal_dhea + sal_test #thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness - -#age factor -agefac =~ age +lh_paracentral_fac =~ lh_paracentral_thickness " +# Fit models +fit_fm2v3_lh_paracentral_cor <- cfa(fm2v3_lh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_middletemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_paracentral_cor <- cfa(fm1v3_lh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_paracentral_cor <- cfa(sr1_lh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness -" -hm2_lh_middletemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_paracentral_cor <- cfa(sr2_lh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_paracentral_cor <- cfa(hm1_lh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_paracentral_cor <- cfa(hm2_lh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_middletemporal_fac =~ lh_middletemporal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_paracentral_cor, fit.measures = T, standardized = T) -####### lh_parahippocampal_thickness ####### +####### lh_parsopercularis_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_parahippocampal_cor <- " +fm2v3_lh_parsopercularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -4816,10 +4643,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_parahippocampal_fac =~ lh_parahippocampal_thickness +lh_parsopercularis_fac =~ lh_parsopercularis_thickness " -fm2v3_lh_parahippocampal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_parsopercularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -4828,12 +4656,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -4845,16 +4674,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_parahippocampal_fac =~ lh_parahippocampal_thickness +#thickness factor +lh_parsopercularis_fac =~ lh_parsopercularis_thickness +" +# Do the same for self-report models only +sr1_lh_parsopercularis_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_parsopercularis_fac =~ lh_parsopercularis_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_parahippocampal_cor <- " +sr2_lh_parsopercularis_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_parsopercularis_fac =~ lh_parsopercularis_thickness +" + +# And for hormone models only +hm1_lh_parsopercularis_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +lh_parsopercularis_fac =~ lh_parsopercularis_thickness +" + +hm2_lh_parsopercularis_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_parsopercularis_fac =~ lh_parsopercularis_thickness +" +# Fit models +fit_fm2v3_lh_parsopercularis_cor <- cfa(fm2v3_lh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_parsopercularis_cor <- cfa(fm1v3_lh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_parsopercularis_cor <- cfa(sr1_lh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_parsopercularis_cor <- cfa(sr2_lh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_parsopercularis_cor <- cfa(hm1_lh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_parsopercularis_cor <- cfa(hm2_lh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_parsopercularis_cor, fit.measures = T, standardized = T) + +####### lh_parsorbitalis_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_parsorbitalis_cor <- " #Latent Variables #Saliva - Level 1 @@ -4863,13 +4767,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -4881,11 +4784,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness " -fm1v3_lh_parahippocampal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_parsorbitalis_cor <- " #Latent Variables #Saliva - Level 1 @@ -4913,55 +4818,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness - -#age factor -agefac =~ age +lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness " - # Do the same for self-report models only -sr1_lh_parahippocampal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness -" - -sr1_lh_parahippocampal_corage <- " +sr1_lh_parsorbitalis_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness - -#age factor -agefac =~ age -" - -sr2_lh_parahippocampal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness +lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness " -sr2_lh_parahippocampal_corage <- " +sr2_lh_parsorbitalis_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness - -#age factor -agefac =~ age +lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness " # And for hormone models only -hm1_lh_parahippocampal_cor <- " +hm1_lh_parsorbitalis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -4971,90 +4849,59 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness +lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness " -hm1_lh_parahippocampal_corage <- " +hm2_lh_parsorbitalis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +adrenal =~ sal_dhea + sal_test #thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness - -#age factor -agefac =~ age +lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness " +# Fit models +fit_fm2v3_lh_parsorbitalis_cor <- cfa(fm2v3_lh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_parahippocampal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_fm1v3_lh_parsorbitalis_cor <- cfa(fm1v3_lh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness -" +fit_sr1_lh_parsorbitalis_cor <- cfa(sr1_lh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_parahippocampal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_parsorbitalis_cor <- cfa(sr2_lh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_parsorbitalis_cor <- cfa(hm1_lh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_parsorbitalis_cor <- cfa(hm2_lh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_parahippocampal_fac =~ lh_parahippocampal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_parsorbitalis_cor, fit.measures = T, standardized = T) -####### lh_paracentral_thickness ####### +####### lh_parstriangularis_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_paracentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_paracentral_fac =~ lh_paracentral_thickness -" - -fm2v3_lh_paracentral_corage <- " +fm2v3_lh_parstriangularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -5082,14 +4929,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_paracentral_fac =~ lh_paracentral_thickness - -#age factor -agefac =~ age +lh_parstriangularis_fac =~ lh_parstriangularis_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_paracentral_cor <- " +fm1v3_lh_parstriangularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -5117,86 +4961,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness +lh_parstriangularis_fac =~ lh_parstriangularis_thickness " +# Do the same for self-report models only +sr1_lh_parstriangularis_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -fm1v3_lh_paracentral_corage <- " -#Latent Variables +#thickness factor +lh_parstriangularis_fac =~ lh_parstriangularis_thickness +" -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_lh_paracentral_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness -" - -sr1_lh_paracentral_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness - -#age factor -agefac =~ age -" - -sr2_lh_paracentral_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness -" - -sr2_lh_paracentral_corage <- " +sr2_lh_parstriangularis_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness - -#age factor -agefac =~ age +lh_parstriangularis_fac =~ lh_parstriangularis_thickness " # And for hormone models only -hm1_lh_paracentral_cor <- " +hm1_lh_parstriangularis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5206,59 +4992,59 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness +lh_parstriangularis_fac =~ lh_parstriangularis_thickness " -hm1_lh_paracentral_corage <- " +hm2_lh_parstriangularis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +adrenal =~ sal_dhea + sal_test #thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness - -#age factor -agefac =~ age +lh_parstriangularis_fac =~ lh_parstriangularis_thickness " +# Fit models +fit_fm2v3_lh_parstriangularis_cor <- cfa(fm2v3_lh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_paracentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_fm1v3_lh_parstriangularis_cor <- cfa(fm1v3_lh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness -" +fit_sr1_lh_parstriangularis_cor <- cfa(sr1_lh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_paracentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_parstriangularis_cor <- cfa(sr2_lh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_parstriangularis_cor <- cfa(hm1_lh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_parstriangularis_cor <- cfa(hm2_lh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_paracentral_fac =~ lh_paracentral_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_parstriangularis_cor, fit.measures = T, standardized = T) -####### lh_parsopercularis_thickness ####### +####### lh_pericalcarine_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_parsopercularis_cor <- " +fm2v3_lh_pericalcarine_cor <- " #Latent Variables #Saliva - Level 1 @@ -5286,10 +5072,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_parsopercularis_fac =~ lh_parsopercularis_thickness +lh_pericalcarine_fac =~ lh_pericalcarine_thickness " -fm2v3_lh_parsopercularis_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_pericalcarine_cor <- " #Latent Variables #Saliva - Level 1 @@ -5298,12 +5085,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -5315,16 +5103,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_parsopercularis_fac =~ lh_parsopercularis_thickness +#thickness factor +lh_pericalcarine_fac =~ lh_pericalcarine_thickness +" +# Do the same for self-report models only +sr1_lh_pericalcarine_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_pericalcarine_fac =~ lh_pericalcarine_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_parsopercularis_cor <- " +sr2_lh_pericalcarine_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_pericalcarine_fac =~ lh_pericalcarine_thickness +" + +# And for hormone models only +hm1_lh_pericalcarine_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +lh_pericalcarine_fac =~ lh_pericalcarine_thickness +" + +hm2_lh_pericalcarine_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_pericalcarine_fac =~ lh_pericalcarine_thickness +" +# Fit models +fit_fm2v3_lh_pericalcarine_cor <- cfa(fm2v3_lh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_pericalcarine_cor <- cfa(fm1v3_lh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_pericalcarine_cor <- cfa(sr1_lh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_pericalcarine_cor <- cfa(sr2_lh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_pericalcarine_cor <- cfa(hm1_lh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_pericalcarine_cor <- cfa(hm2_lh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_pericalcarine_cor, fit.measures = T, standardized = T) + +####### lh_postcentral_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_postcentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -5333,13 +5196,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -5351,11 +5213,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_postcentral_fac =~ lh_postcentral_thickness " -fm1v3_lh_parsopercularis_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_postcentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -5383,68 +5247,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness - -#age factor -agefac =~ age +lh_postcentral_fac =~ lh_postcentral_thickness " - # Do the same for self-report models only -sr1_lh_parsopercularis_cor <- " +sr1_lh_postcentral_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness +lh_postcentral_fac =~ lh_postcentral_thickness " -sr1_lh_parsopercularis_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness - -#age factor -agefac =~ age -" - -sr2_lh_parsopercularis_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness -" - -sr2_lh_parsopercularis_corage <- " +sr2_lh_postcentral_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness - -#age factor -agefac =~ age +lh_postcentral_fac =~ lh_postcentral_thickness " # And for hormone models only -hm1_lh_parsopercularis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness -" - -hm1_lh_parsopercularis_corage <- " +hm1_lh_postcentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5454,13 +5278,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness - -#age factor -agefac =~ age +lh_postcentral_fac =~ lh_postcentral_thickness " -hm2_lh_parsopercularis_cor <- " +hm2_lh_postcentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5470,62 +5291,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness +lh_postcentral_fac =~ lh_postcentral_thickness " +# Fit models +fit_fm2v3_lh_postcentral_cor <- cfa(fm2v3_lh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_parsopercularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_postcentral_cor <- cfa(fm1v3_lh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_postcentral_cor <- cfa(sr1_lh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_parsopercularis_fac =~ lh_parsopercularis_thickness +fit_sr2_lh_postcentral_cor <- cfa(sr2_lh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_postcentral_cor <- cfa(hm1_lh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_postcentral_cor <- cfa(hm2_lh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -####### lh_parsorbitalis_thickness ####### +# Summary Stats for models +summary(fit_fm2v3_lh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_postcentral_cor, fit.measures = T, standardized = T) + +####### lh_posteriorcingulate_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_parsorbitalis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness -" - -fm2v3_lh_parsorbitalis_corage <- " +fm2v3_lh_posteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -5553,45 +5358,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness - -#age factor -agefac =~ age +lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_parsorbitalis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness -" - -fm1v3_lh_parsorbitalis_corage <- " +fm1v3_lh_posteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -5619,68 +5390,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness - -#age factor -agefac =~ age +lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness " - # Do the same for self-report models only -sr1_lh_parsorbitalis_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness -" - -sr1_lh_parsorbitalis_corage <- " +sr1_lh_posteriorcingulate_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -sr2_lh_parsorbitalis_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness +lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness " -sr2_lh_parsorbitalis_corage <- " +sr2_lh_posteriorcingulate_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness - -#age factor -agefac =~ age +lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness " # And for hormone models only -hm1_lh_parsorbitalis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness -" - -hm1_lh_parsorbitalis_corage <- " +hm1_lh_posteriorcingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5690,13 +5421,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness - -#age factor -agefac =~ age +lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness " -hm2_lh_parsorbitalis_cor <- " +hm2_lh_posteriorcingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5706,31 +5434,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness +lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness " +# Fit models +fit_fm2v3_lh_posteriorcingulate_cor <- cfa(fm2v3_lh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_parsorbitalis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_posteriorcingulate_cor <- cfa(fm1v3_lh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_sr1_lh_posteriorcingulate_cor <- cfa(sr1_lh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_parsorbitalis_fac =~ lh_parsorbitalis_thickness +fit_sr2_lh_posteriorcingulate_cor <- cfa(sr2_lh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_posteriorcingulate_cor <- cfa(hm1_lh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_posteriorcingulate_cor <- cfa(hm2_lh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -####### lh_parstriangularis_thickness ####### +# Summary Stats for models +summary(fit_fm2v3_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) + +####### lh_precentral_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_parstriangularis_cor <- " +fm2v3_lh_precentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -5758,10 +5501,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +lh_precentral_fac =~ lh_precentral_thickness " -fm2v3_lh_parstriangularis_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_precentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -5770,12 +5514,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -5787,16 +5532,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +#thickness factor +lh_precentral_fac =~ lh_precentral_thickness +" +# Do the same for self-report models only +sr1_lh_precentral_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_precentral_fac =~ lh_precentral_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_parstriangularis_cor <- " +sr2_lh_precentral_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_precentral_fac =~ lh_precentral_thickness +" + +# And for hormone models only +hm1_lh_precentral_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +lh_precentral_fac =~ lh_precentral_thickness +" + +hm2_lh_precentral_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_precentral_fac =~ lh_precentral_thickness +" +# Fit models +fit_fm2v3_lh_precentral_cor <- cfa(fm2v3_lh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_precentral_cor <- cfa(fm1v3_lh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_precentral_cor <- cfa(sr1_lh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_precentral_cor <- cfa(sr2_lh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_precentral_cor <- cfa(hm1_lh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_precentral_cor <- cfa(hm2_lh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_precentral_cor, fit.measures = T, standardized = T) + +####### lh_precuneus_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_precuneus_cor <- " #Latent Variables #Saliva - Level 1 @@ -5805,13 +5625,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -5823,11 +5642,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_precuneus_fac =~ lh_precuneus_thickness " -fm1v3_lh_parstriangularis_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_precuneus_cor <- " #Latent Variables #Saliva - Level 1 @@ -5855,54 +5676,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness - -#age factor -agefac =~ age +lh_precuneus_fac =~ lh_precuneus_thickness " # Do the same for self-report models only -sr1_lh_parstriangularis_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness -" - -sr2_lh_parstriangularis_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness -" - -sr1_lh_parstriangularis_corage <- " +sr1_lh_precuneus_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness - -#age factor -agefac =~ age +lh_precuneus_fac =~ lh_precuneus_thickness " -sr2_lh_parstriangularis_corage <- " +sr2_lh_precuneus_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness - -#age factor -agefac =~ age +lh_precuneus_fac =~ lh_precuneus_thickness " # And for hormone models only -hm1_lh_parstriangularis_cor <- " +hm1_lh_precuneus_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5912,10 +5707,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +lh_precuneus_fac =~ lh_precuneus_thickness " -hm2_lh_parstriangularis_cor <- " +hm2_lh_precuneus_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -5925,45 +5720,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +lh_precuneus_fac =~ lh_precuneus_thickness " +# Fit models +fit_fm2v3_lh_precuneus_cor <- cfa(fm2v3_lh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_parstriangularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +fit_fm1v3_lh_precuneus_cor <- cfa(fm1v3_lh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +fit_sr1_lh_precuneus_cor <- cfa(sr1_lh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr2_lh_precuneus_cor <- cfa(sr2_lh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_precuneus_cor <- cfa(hm1_lh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_parstriangularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_hm2_lh_precuneus_cor <- cfa(hm2_lh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test -#thickness factor -lh_parstriangularis_fac =~ lh_parstriangularis_thickness +# Summary Stats for models +summary(fit_fm2v3_lh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_precuneus_cor, fit.measures = T, standardized = T) -#age factor -agefac =~ age -" -####### lh_pericalcarine_thickness ####### +####### lh_rostralanteriorcingulate_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_pericalcarine_cor <- " +fm2v3_lh_rostralanteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -5991,10 +5787,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_pericalcarine_fac =~ lh_pericalcarine_thickness +lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness " -fm2v3_lh_pericalcarine_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_rostralanteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -6003,12 +5800,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -6020,33 +5818,107 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_pericalcarine_fac =~ lh_pericalcarine_thickness +#thickness factor +lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +" +# Do the same for self-report models only +sr1_lh_rostralanteriorcingulate_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_pericalcarine_cor <- " -#Latent Variables +sr2_lh_rostralanteriorcingulate_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +" +# And for hormone models only +hm1_lh_rostralanteriorcingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +#thickness factor +lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +" -#Covariances for Saliva Sample Day +hm2_lh_rostralanteriorcingulate_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +" +# Fit models +fit_fm2v3_lh_rostralanteriorcingulate_cor <- cfa(fm2v3_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_rostralanteriorcingulate_cor <- cfa(fm1v3_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_rostralanteriorcingulate_cor <- cfa(sr1_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_rostralanteriorcingulate_cor <- cfa(sr2_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_rostralanteriorcingulate_cor <- cfa(hm1_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_rostralanteriorcingulate_cor <- cfa(hm2_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) + +####### lh_rostralmiddlefrontal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_rostralmiddlefrontal_cor <- " +#Latent Variables + +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Self-Report +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr + +#Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 estr1 ~~ test1 dhea2 ~~ estr2 + test2 @@ -6056,11 +5928,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness " -fm1v3_lh_pericalcarine_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_rostralmiddlefrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6088,55 +5962,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness - -#age factor -agefac =~ age +lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness " - # Do the same for self-report models only -sr1_lh_pericalcarine_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness -" - -sr2_lh_pericalcarine_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness -" - -sr1_lh_pericalcarine_corage <- " +sr1_lh_rostralmiddlefrontal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness - -#age factor -agefac =~ age +lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness " -sr2_lh_pericalcarine_corage <- " +sr2_lh_rostralmiddlefrontal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness - -#age factor -agefac =~ age +lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness " # And for hormone models only -hm1_lh_pericalcarine_cor <- " +hm1_lh_rostralmiddlefrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6146,10 +5993,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness +lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness " -hm2_lh_pericalcarine_cor <- " +hm2_lh_rostralmiddlefrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6159,77 +6006,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness +lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness " +# Fit models +fit_fm2v3_lh_rostralmiddlefrontal_cor <- cfa(fm2v3_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_pericalcarine_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness +fit_fm1v3_lh_rostralmiddlefrontal_cor <- cfa(fm1v3_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_lh_rostralmiddlefrontal_cor <- cfa(sr1_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_pericalcarine_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_rostralmiddlefrontal_cor <- cfa(sr2_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_rostralmiddlefrontal_cor <- cfa(hm1_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_rostralmiddlefrontal_cor <- cfa(hm2_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_pericalcarine_fac =~ lh_pericalcarine_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -####### lh_postcentral_thickness ####### +####### lh_superiorfrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_postcentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_postcentral_fac =~ lh_postcentral_thickness -" - -fm2v3_lh_postcentral_corage <- " +fm2v3_lh_superiorfrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6257,45 +6073,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_postcentral_fac =~ lh_postcentral_thickness - -#age factor -agefac =~ age +lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_postcentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness -" - -fm1v3_lh_postcentral_corage <- " +fm1v3_lh_superiorfrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6323,54 +6105,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness - -#age factor -agefac =~ age +lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness " - # Do the same for self-report models only -sr1_lh_postcentral_cor <- " +sr1_lh_superiorfrontal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness +lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness " -sr2_lh_postcentral_cor <- " +sr2_lh_superiorfrontal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness -" -sr1_lh_postcentral_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness - -#age factor -agefac =~ age -" - -sr2_lh_postcentral_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness - -#age factor -agefac =~ age +lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness " # And for hormone models only -hm1_lh_postcentral_cor <- " +hm1_lh_superiorfrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6380,10 +6136,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness +lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness " -hm2_lh_postcentral_cor <- " +hm2_lh_superiorfrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6393,76 +6149,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness +lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness " -hm1_lh_postcentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +# Fit models +fit_fm2v3_lh_superiorfrontal_cor <- cfa(fm2v3_lh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness +fit_fm1v3_lh_superiorfrontal_cor <- cfa(fm1v3_lh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_lh_superiorfrontal_cor <- cfa(sr1_lh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_postcentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_superiorfrontal_cor <- cfa(sr2_lh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_superiorfrontal_cor <- cfa(hm1_lh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_superiorfrontal_cor <- cfa(hm2_lh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_postcentral_fac =~ lh_postcentral_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_superiorfrontal_cor, fit.measures = T, standardized = T) -####### lh_posteriorcingulate_thickness ####### +####### lh_superiorparietal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_posteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness -" - -fm2v3_lh_posteriorcingulate_corage <- " +fm2v3_lh_superiorparietal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6490,45 +6216,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness - -#age factor -agefac =~ age +lh_superiorparietal_fac =~ lh_superiorparietal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_posteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness -" - -fm1v3_lh_posteriorcingulate_corage <- " +fm1v3_lh_superiorparietal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6556,55 +6248,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness - -#age factor -agefac =~ age +lh_superiorparietal_fac =~ lh_superiorparietal_thickness " - # Do the same for self-report models only -sr1_lh_posteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness -" - -sr2_lh_posteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness -" - -sr1_lh_posteriorcingulate_corage <- " +sr1_lh_superiorparietal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness - -#age factor -agefac =~ age +lh_superiorparietal_fac =~ lh_superiorparietal_thickness " -sr2_lh_posteriorcingulate_corage <- " +sr2_lh_superiorparietal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness - -#age factor -agefac =~ age +lh_superiorparietal_fac =~ lh_superiorparietal_thickness " # And for hormone models only -hm1_lh_posteriorcingulate_cor <- " +hm1_lh_superiorparietal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6614,10 +6279,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness +lh_superiorparietal_fac =~ lh_superiorparietal_thickness " -hm2_lh_posteriorcingulate_cor <- " +hm2_lh_superiorparietal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6627,46 +6292,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness +lh_superiorparietal_fac =~ lh_superiorparietal_thickness " +# Fit models +fit_fm2v3_lh_superiorparietal_cor <- cfa(fm2v3_lh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_posteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness +fit_fm1v3_lh_superiorparietal_cor <- cfa(fm1v3_lh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_lh_superiorparietal_cor <- cfa(sr1_lh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_posteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_superiorparietal_cor <- cfa(sr2_lh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_superiorparietal_cor <- cfa(hm1_lh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_superiorparietal_cor <- cfa(hm2_lh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_posteriorcingulate_fac =~ lh_posteriorcingulate_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_superiorparietal_cor, fit.measures = T, standardized = T) -####### lh_precentral_thickness ####### +####### lh_superiortemporal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_precentral_cor <- " +fm2v3_lh_superiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6694,10 +6359,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_precentral_fac =~ lh_precentral_thickness +lh_superiortemporal_fac =~ lh_superiortemporal_thickness " -fm2v3_lh_precentral_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_superiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6706,12 +6372,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -6723,16 +6390,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_precentral_fac =~ lh_precentral_thickness - -#age factor -agefac =~ age +#thickness factor +lh_superiortemporal_fac =~ lh_superiortemporal_thickness " - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_precentral_cor <- " +# Do the same for self-report models only +sr1_lh_superiortemporal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#thickness factor +lh_superiortemporal_fac =~ lh_superiortemporal_thickness +" + +sr2_lh_superiortemporal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_superiortemporal_fac =~ lh_superiortemporal_thickness +" + +# And for hormone models only +hm1_lh_superiortemporal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +lh_superiortemporal_fac =~ lh_superiortemporal_thickness +" + +hm2_lh_superiortemporal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_superiortemporal_fac =~ lh_superiortemporal_thickness +" +# Fit models +fit_fm2v3_lh_superiortemporal_cor <- cfa(fm2v3_lh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_superiortemporal_cor <- cfa(fm1v3_lh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_superiortemporal_cor <- cfa(sr1_lh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_superiortemporal_cor <- cfa(sr2_lh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_superiortemporal_cor <- cfa(hm1_lh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_superiortemporal_cor <- cfa(hm2_lh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_superiortemporal_cor, fit.measures = T, standardized = T) + +####### lh_supramarginal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_supramarginal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6741,13 +6483,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -6759,11 +6500,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_precentral_fac =~ lh_precentral_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_supramarginal_fac =~ lh_supramarginal_thickness " -fm1v3_lh_precentral_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_supramarginal_cor <- " #Latent Variables #Saliva - Level 1 @@ -6791,55 +6534,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_precentral_fac =~ lh_precentral_thickness - -#age factor -agefac =~ age +lh_supramarginal_fac =~ lh_supramarginal_thickness " - # Do the same for self-report models only -sr1_lh_precentral_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_precentral_fac =~ lh_precentral_thickness -" - -sr2_lh_precentral_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_precentral_fac =~ lh_precentral_thickness -" - -sr1_lh_precentral_corage <- " +sr1_lh_supramarginal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_precentral_fac =~ lh_precentral_thickness - -#age factor -agefac =~ age +lh_supramarginal_fac =~ lh_supramarginal_thickness " -sr2_lh_precentral_corage <- " +sr2_lh_supramarginal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_precentral_fac =~ lh_precentral_thickness - -#age factor -agefac =~ age +lh_supramarginal_fac =~ lh_supramarginal_thickness " # And for hormone models only -hm1_lh_precentral_cor <- " +hm1_lh_supramarginal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6849,10 +6565,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_precentral_fac =~ lh_precentral_thickness +lh_supramarginal_fac =~ lh_supramarginal_thickness " -hm2_lh_precentral_cor <- " +hm2_lh_supramarginal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -6862,46 +6578,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_precentral_fac =~ lh_precentral_thickness +lh_supramarginal_fac =~ lh_supramarginal_thickness " +# Fit models +fit_fm2v3_lh_supramarginal_cor <- cfa(fm2v3_lh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_precentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_precentral_fac =~ lh_precentral_thickness +fit_fm1v3_lh_supramarginal_cor <- cfa(fm1v3_lh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_lh_supramarginal_cor <- cfa(sr1_lh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_precentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_supramarginal_cor <- cfa(sr2_lh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_supramarginal_cor <- cfa(hm1_lh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_supramarginal_cor <- cfa(hm2_lh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_precentral_fac =~ lh_precentral_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_supramarginal_cor, fit.measures = T, standardized = T) -####### lh_precuneus_thickness ####### +####### lh_frontalpole_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_precuneus_cor <- " +fm2v3_lh_frontalpole_cor <- " #Latent Variables #Saliva - Level 1 @@ -6929,10 +6645,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_precuneus_fac =~ lh_precuneus_thickness +lh_frontalpole_fac =~ lh_frontalpole_thickness " -fm2v3_lh_precuneus_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_frontalpole_cor <- " #Latent Variables #Saliva - Level 1 @@ -6941,12 +6658,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -6958,49 +6676,125 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_precuneus_fac =~ lh_precuneus_thickness +#thickness factor +lh_frontalpole_fac =~ lh_frontalpole_thickness +" +# Do the same for self-report models only +sr1_lh_frontalpole_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +lh_frontalpole_fac =~ lh_frontalpole_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_precuneus_cor <- " -#Latent Variables +sr2_lh_frontalpole_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +lh_frontalpole_fac =~ lh_frontalpole_thickness +" +# And for hormone models only +hm1_lh_frontalpole_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness +lh_frontalpole_fac =~ lh_frontalpole_thickness " -fm1v3_lh_precuneus_corage <- " -#Latent Variables - +hm2_lh_frontalpole_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +lh_frontalpole_fac =~ lh_frontalpole_thickness +" +# Fit models +fit_fm2v3_lh_frontalpole_cor <- cfa(fm2v3_lh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_lh_frontalpole_cor <- cfa(fm1v3_lh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_lh_frontalpole_cor <- cfa(sr1_lh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_lh_frontalpole_cor <- cfa(sr2_lh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_frontalpole_cor <- cfa(hm1_lh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_lh_frontalpole_cor <- cfa(hm2_lh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_lh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_frontalpole_cor, fit.measures = T, standardized = T) + +####### lh_temporalpole_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_lh_temporalpole_cor <- " +#Latent Variables + +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Self-Report +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr + +#Covariances for Saliva Sample Day +dhea1 ~~ estr1 + test1 +estr1 ~~ test1 +dhea2 ~~ estr2 + test2 +estr2 ~~ test2 +dhea3 ~~ estr3 + test3 +estr3 ~~ test3 +dhea4 ~~ estr4 + test4 +estr4 ~~ test4 + +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +lh_temporalpole_fac =~ lh_temporalpole_thickness +" + +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_lh_temporalpole_cor <- " +#Latent Variables + #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7026,55 +6820,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness - -#age factor -agefac =~ age +lh_temporalpole_fac =~ lh_temporalpole_thickness " - # Do the same for self-report models only -sr1_lh_precuneus_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness -" - -sr2_lh_precuneus_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness -" - -sr1_lh_precuneus_corage <- " +sr1_lh_temporalpole_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness - -#age factor -agefac =~ age +lh_temporalpole_fac =~ lh_temporalpole_thickness " -sr2_lh_precuneus_corage <- " +sr2_lh_temporalpole_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness - -#age factor -agefac =~ age +lh_temporalpole_fac =~ lh_temporalpole_thickness " # And for hormone models only -hm1_lh_precuneus_cor <- " +hm1_lh_temporalpole_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7084,10 +6851,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness +lh_temporalpole_fac =~ lh_temporalpole_thickness " -hm2_lh_precuneus_cor <- " +hm2_lh_temporalpole_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7097,46 +6864,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness +lh_temporalpole_fac =~ lh_temporalpole_thickness " +# Fit models +fit_fm2v3_lh_temporalpole_cor <- cfa(fm2v3_lh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_precuneus_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness +fit_fm1v3_lh_temporalpole_cor <- cfa(fm1v3_lh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_lh_temporalpole_cor <- cfa(sr1_lh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_precuneus_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_temporalpole_cor <- cfa(sr2_lh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_temporalpole_cor <- cfa(hm1_lh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_temporalpole_cor <- cfa(hm2_lh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_precuneus_fac =~ lh_precuneus_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_temporalpole_cor, fit.measures = T, standardized = T) -####### lh_rostralanteriorcingulate_thickness ####### +####### lh_transversetemporal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_rostralanteriorcingulate_cor <- " +fm2v3_lh_transversetemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -7164,75 +6931,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +lh_transversetemporal_fac =~ lh_transversetemporal_thickness " -fm2v3_lh_rostralanteriorcingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_rostralanteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness -" - -fm1v3_lh_rostralanteriorcingulate_corage <- " +fm1v3_lh_transversetemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -7260,55 +6963,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age +lh_transversetemporal_fac =~ lh_transversetemporal_thickness " - # Do the same for self-report models only -sr1_lh_rostralanteriorcingulate_cor <- " +sr1_lh_transversetemporal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +lh_transversetemporal_fac =~ lh_transversetemporal_thickness " -sr2_lh_rostralanteriorcingulate_cor <- " +sr2_lh_transversetemporal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness -" - -sr1_lh_rostralanteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -sr2_lh_rostralanteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age +lh_transversetemporal_fac =~ lh_transversetemporal_thickness " # And for hormone models only -hm1_lh_rostralanteriorcingulate_cor <- " +hm1_lh_transversetemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7318,10 +6994,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +lh_transversetemporal_fac =~ lh_transversetemporal_thickness " -hm2_lh_rostralanteriorcingulate_cor <- " +hm2_lh_transversetemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7331,77 +7007,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +lh_transversetemporal_fac =~ lh_transversetemporal_thickness " +# Fit models +fit_fm2v3_lh_transversetemporal_cor <- cfa(fm2v3_lh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_rostralanteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness +fit_fm1v3_lh_transversetemporal_cor <- cfa(fm1v3_lh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_lh_transversetemporal_cor <- cfa(sr1_lh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_rostralanteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_lh_transversetemporal_cor <- cfa(sr2_lh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_transversetemporal_cor <- cfa(hm1_lh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_lh_transversetemporal_cor <- cfa(hm2_lh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_rostralanteriorcingulate_fac =~ lh_rostralanteriorcingulate_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_lh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_transversetemporal_cor, fit.measures = T, standardized = T) -####### lh_rostralmiddlefrontal_thickness ####### +####### lh_insula_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_rostralmiddlefrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness -" - -fm2v3_lh_rostralmiddlefrontal_corage <- " +fm2v3_lh_insula_cor <- " #Latent Variables #Saliva - Level 1 @@ -7429,45 +7074,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age +lh_insula_fac =~ lh_insula_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_rostralmiddlefrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness -" - -fm1v3_lh_rostralmiddlefrontal_corage <- " +fm1v3_lh_insula_cor <- " #Latent Variables #Saliva - Level 1 @@ -7495,55 +7106,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age +lh_insula_fac =~ lh_insula_thickness " - # Do the same for self-report models only -sr1_lh_rostralmiddlefrontal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness -" - -sr2_lh_rostralmiddlefrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness -" - -sr1_lh_rostralmiddlefrontal_corage <- " +sr1_lh_insula_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age +lh_insula_fac =~ lh_insula_thickness " -sr2_lh_rostralmiddlefrontal_corage <- " +sr2_lh_insula_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age +lh_insula_fac =~ lh_insula_thickness " # And for hormone models only -hm1_lh_rostralmiddlefrontal_cor <- " +hm1_lh_insula_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7553,10 +7137,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness +lh_insula_fac =~ lh_insula_thickness " -hm2_lh_rostralmiddlefrontal_cor <- " +hm2_lh_insula_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7566,46 +7150,48 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness +lh_insula_fac =~ lh_insula_thickness " +# Fit models +fit_fm2v3_lh_insula_cor <- cfa(fm2v3_lh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_rostralmiddlefrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_fm1v3_lh_insula_cor <- cfa(fm1v3_lh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +fit_sr1_lh_insula_cor <- cfa(sr1_lh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness +fit_sr2_lh_insula_cor <- cfa(sr2_lh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_lh_insula_cor <- cfa(hm1_lh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_hm2_lh_insula_cor <- cfa(hm2_lh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_rostralmiddlefrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +# Summary Stats for models +summary(fit_fm2v3_lh_insula_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_lh_insula_cor, fit.measures = T, standardized = T) +summary(fit_sr1_lh_insula_cor, fit.measures = T, standardized = T) +summary(fit_sr2_lh_insula_cor, fit.measures = T, standardized = T) +summary(fit_hm1_lh_insula_cor, fit.measures = T, standardized = T) +summary(fit_hm2_lh_insula_cor, fit.measures = T, standardized = T) -#thickness factor -lh_rostralmiddlefrontal_fac =~ lh_rostralmiddlefrontal_thickness -#age factor -agefac =~ age -" -####### lh_superiorfrontal_thickness ####### +####### rh_bankssts_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_superiorfrontal_cor <- " +fm2v3_rh_bankssts_cor <- " #Latent Variables #Saliva - Level 1 @@ -7633,10 +7219,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness +rh_bankssts_fac =~ rh_bankssts_thickness " -fm2v3_lh_superiorfrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_bankssts_cor <- " #Latent Variables #Saliva - Level 1 @@ -7645,12 +7232,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -7662,16 +7250,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness +#thickness factor +rh_bankssts_fac =~ rh_bankssts_thickness +" +# Do the same for self-report models only +sr1_rh_bankssts_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_bankssts_fac =~ rh_bankssts_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_superiorfrontal_cor <- " +sr2_rh_bankssts_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_bankssts_fac =~ rh_bankssts_thickness +" + +# And for hormone models only +hm1_rh_bankssts_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_bankssts_fac =~ rh_bankssts_thickness +" + +hm2_rh_bankssts_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_bankssts_fac =~ rh_bankssts_thickness +" +# Fit models +fit_fm2v3_rh_bankssts_cor <- cfa(fm2v3_rh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_bankssts_cor <- cfa(fm1v3_rh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_bankssts_cor <- cfa(sr1_rh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_bankssts_cor <- cfa(sr2_rh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_bankssts_cor <- cfa(hm1_rh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_bankssts_cor <- cfa(hm2_rh_bankssts_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_bankssts_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_bankssts_cor, fit.measures = T, standardized = T) + +####### rh_caudalanteriorcingulate_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_caudalanteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -7680,13 +7343,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -7698,11 +7360,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness " -fm1v3_lh_superiorfrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_caudalanteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -7730,80 +7394,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness - -#age factor -agefac =~ age +rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness " # Do the same for self-report models only -sr1_lh_superiorfrontal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness -" - -sr2_lh_superiorfrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness -" - -sr1_lh_superiorfrontal_corage <- " +sr1_rh_caudalanteriorcingulate_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness - -#age factor -agefac =~ age +rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness " -sr2_lh_superiorfrontal_corage <- " +sr2_rh_caudalanteriorcingulate_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness - -#age factor -agefac =~ age +rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness " # And for hormone models only -hm1_lh_superiorfrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness -" - -hm2_lh_superiorfrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness -" - -hm1_lh_superiorfrontal_corage <- " +hm1_rh_caudalanteriorcingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7813,13 +7425,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness - -#age factor -agefac =~ age +rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness " -hm2_lh_superiorfrontal_corage <- " +hm2_rh_caudalanteriorcingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -7829,48 +7438,34 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_superiorfrontal_fac =~ lh_superiorfrontal_thickness - -#age factor -agefac =~ age +rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness " +# Fit models +fit_fm2v3_rh_caudalanteriorcingulate_cor <- cfa(fm2v3_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_rh_caudalanteriorcingulate_cor <- cfa(fm1v3_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_rh_caudalanteriorcingulate_cor <- cfa(sr1_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_rh_caudalanteriorcingulate_cor <- cfa(sr2_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_rh_caudalanteriorcingulate_cor <- cfa(hm1_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_rh_caudalanteriorcingulate_cor <- cfa(hm2_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +# Summary Stats for models +summary(fit_fm2v3_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -####### lh_superiorparietal_thickness ####### +####### rh_caudalmiddlefrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_superiorparietal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_superiorparietal_fac =~ lh_superiorparietal_thickness -" - -fm2v3_lh_superiorparietal_corage <- " +fm2v3_rh_caudalmiddlefrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -7898,14 +7493,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_superiorparietal_fac =~ lh_superiorparietal_thickness - -#age factor -agefac =~ age +rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_superiorparietal_cor <- " +fm1v3_rh_caudalmiddlefrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -7933,86 +7525,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness +rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness " +# Do the same for self-report models only +sr1_rh_caudalmiddlefrontal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -fm1v3_lh_superiorparietal_corage <- " -#Latent Variables +#thickness factor +rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +" + +sr2_rh_caudalmiddlefrontal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_lh_superiorparietal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness -" - -sr2_lh_superiorparietal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness -" - -sr1_lh_superiorparietal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -sr2_lh_superiorparietal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_lh_superiorparietal_cor <- " +#thickness factor +rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +" + +# And for hormone models only +hm1_rh_caudalmiddlefrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8022,10 +7556,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness +rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness " -hm2_lh_superiorparietal_cor <- " +hm2_rh_caudalmiddlefrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8035,46 +7569,35 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness -" - -hm1_lh_superiorparietal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness - -#age factor -agefac =~ age +rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness " +# Fit models +fit_fm2v3_rh_caudalmiddlefrontal_cor <- cfa(fm2v3_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_fm1v3_rh_caudalmiddlefrontal_cor <- cfa(fm1v3_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr1_rh_caudalmiddlefrontal_cor <- cfa(sr1_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_sr2_rh_caudalmiddlefrontal_cor <- cfa(sr2_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm1_rh_caudalmiddlefrontal_cor <- cfa(hm1_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) +fit_hm2_rh_caudalmiddlefrontal_cor <- cfa(hm2_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T) -hm2_lh_superiorparietal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -lh_superiorparietal_fac =~ lh_superiorparietal_thickness - -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -####### lh_superiortemporal_thickness ####### +####### rh_cuneus_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_superiortemporal_cor <- " +fm2v3_rh_cuneus_cor <- " #Latent Variables #Saliva - Level 1 @@ -8102,10 +7625,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +rh_cuneus_fac =~ rh_cuneus_thickness " -fm2v3_lh_superiortemporal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_cuneus_cor <- " #Latent Variables #Saliva - Level 1 @@ -8114,12 +7638,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -8131,16 +7656,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +#thickness factor +rh_cuneus_fac =~ rh_cuneus_thickness +" +# Do the same for self-report models only +sr1_rh_cuneus_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_cuneus_fac =~ rh_cuneus_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_superiortemporal_cor <- " +sr2_rh_cuneus_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_cuneus_fac =~ rh_cuneus_thickness +" + +# And for hormone models only +hm1_rh_cuneus_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_cuneus_fac =~ rh_cuneus_thickness +" + +hm2_rh_cuneus_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_cuneus_fac =~ rh_cuneus_thickness +" +# Fit models +fit_fm2v3_rh_cuneus_cor <- cfa(fm2v3_rh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_cuneus_cor <- cfa(fm1v3_rh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_cuneus_cor <- cfa(sr1_rh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_cuneus_cor <- cfa(sr2_rh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_cuneus_cor <- cfa(hm1_rh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_cuneus_cor <- cfa(hm2_rh_cuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_cuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_cuneus_cor, fit.measures = T, standardized = T) + +####### rh_entorhinal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_entorhinal_cor <- " #Latent Variables #Saliva - Level 1 @@ -8149,13 +7749,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -8167,11 +7766,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_entorhinal_fac =~ rh_entorhinal_thickness " -fm1v3_lh_superiortemporal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_entorhinal_cor <- " #Latent Variables #Saliva - Level 1 @@ -8199,55 +7800,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness - -#age factor -agefac =~ age +rh_entorhinal_fac =~ rh_entorhinal_thickness " - # Do the same for self-report models only -sr1_lh_superiortemporal_cor <- " +sr1_rh_entorhinal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +rh_entorhinal_fac =~ rh_entorhinal_thickness " -sr2_lh_superiortemporal_cor <- " +sr2_rh_entorhinal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness -" - -sr1_lh_superiortemporal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -sr2_lh_superiortemporal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness - -#age factor -agefac =~ age +rh_entorhinal_fac =~ rh_entorhinal_thickness " # And for hormone models only -hm1_lh_superiortemporal_cor <- " +hm1_rh_entorhinal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8257,10 +7831,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +rh_entorhinal_fac =~ rh_entorhinal_thickness " -hm2_lh_superiortemporal_cor <- " +hm2_rh_entorhinal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8270,77 +7844,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +rh_entorhinal_fac =~ rh_entorhinal_thickness " +# Fit models +fit_fm2v3_rh_entorhinal_cor <- cfa(fm2v3_rh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_superiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness +fit_fm1v3_rh_entorhinal_cor <- cfa(fm1v3_rh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_entorhinal_cor <- cfa(sr1_rh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_superiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_entorhinal_cor <- cfa(sr2_rh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_entorhinal_cor <- cfa(hm1_rh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_entorhinal_cor <- cfa(hm2_rh_entorhinal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_superiortemporal_fac =~ lh_superiortemporal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_entorhinal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_entorhinal_cor, fit.measures = T, standardized = T) -####### lh_supramarginal_thickness ####### +####### rh_fusiform_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_supramarginal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_supramarginal_fac =~ lh_supramarginal_thickness -" - -fm2v3_lh_supramarginal_corage <- " +fm2v3_rh_fusiform_cor <- " #Latent Variables #Saliva - Level 1 @@ -8368,45 +7911,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_supramarginal_fac =~ lh_supramarginal_thickness - -#age factor -agefac =~ age +rh_fusiform_fac =~ rh_fusiform_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_supramarginal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness -" - -fm1v3_lh_supramarginal_corage <- " +fm1v3_rh_fusiform_cor <- " #Latent Variables #Saliva - Level 1 @@ -8434,55 +7943,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness - -#age factor -agefac =~ age +rh_fusiform_fac =~ rh_fusiform_thickness " - # Do the same for self-report models only -sr1_lh_supramarginal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness -" - -sr2_lh_supramarginal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness -" - -sr1_lh_supramarginal_corage <- " +sr1_rh_fusiform_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness - -#age factor -agefac =~ age +rh_fusiform_fac =~ rh_fusiform_thickness " -sr2_lh_supramarginal_corage <- " +sr2_rh_fusiform_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness - -#age factor -agefac =~ age +rh_fusiform_fac =~ rh_fusiform_thickness " # And for hormone models only -hm1_lh_supramarginal_cor <- " +hm1_rh_fusiform_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8492,10 +7974,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness +rh_fusiform_fac =~ rh_fusiform_thickness " -hm2_lh_supramarginal_cor <- " +hm2_rh_fusiform_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8505,46 +7987,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness +rh_fusiform_fac =~ rh_fusiform_thickness " +# Fit models +fit_fm2v3_rh_fusiform_cor <- cfa(fm2v3_rh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_supramarginal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness +fit_fm1v3_rh_fusiform_cor <- cfa(fm1v3_rh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_fusiform_cor <- cfa(sr1_rh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_supramarginal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_fusiform_cor <- cfa(sr2_rh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_fusiform_cor <- cfa(hm1_rh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_fusiform_cor <- cfa(hm2_rh_fusiform_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_supramarginal_fac =~ lh_supramarginal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_fusiform_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_fusiform_cor, fit.measures = T, standardized = T) -####### lh_frontalpole_thickness ####### +####### left inferior parietal ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_frontalpole_cor <- " +fm2v3_rh_inferiorparietal_cor <- " #Latent Variables #Saliva - Level 1 @@ -8556,7 +8038,7 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal_sr =~ PDS2 + PDS3 + PBIP2 gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +#Neuroendocrine Systems (Saliva + Qs) - Level 3 adrenal =~ sal_dhea + sal_test + adrenal_sr gonadal =~ sal_estr + gonadal_sr @@ -8572,10 +8054,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_frontalpole_fac =~ lh_frontalpole_thickness +rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness " -fm2v3_lh_frontalpole_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_inferiorparietal_cor <- " #Latent Variables #Saliva - Level 1 @@ -8584,12 +8067,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -8601,16 +8085,90 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_frontalpole_fac =~ lh_frontalpole_thickness +#thickness factor +rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +" +# Do the same for self-report models only +sr1_rh_inferiorparietal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_frontalpole_cor <- " +sr2_rh_inferiorparietal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +" +# And for hormone models only +hm1_rh_inferiorparietal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +" + +hm2_rh_inferiorparietal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +" +# Fit models +fit_fm2v3_rh_inferiorparietal_cor <- cfa(fm2v3_rh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_inferiorparietal_cor <- cfa(fm1v3_rh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_inferiorparietal_cor <- cfa(sr1_rh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_inferiorparietal_cor <- cfa(sr2_rh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_inferiorparietal_cor <- cfa(hm1_rh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_inferiorparietal_cor <- cfa(hm2_rh_inferiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_inferiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_inferiorparietal_cor, fit.measures = T, standardized = T) + +####### rh_inferiortemporal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_inferiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -8619,13 +8177,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -8637,11 +8194,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness " -fm1v3_lh_frontalpole_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_inferiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -8669,55 +8228,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness - -#age factor -agefac =~ age +rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness " - # Do the same for self-report models only -sr1_lh_frontalpole_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness -" - -sr2_lh_frontalpole_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness -" - -sr1_lh_frontalpole_corage <- " +sr1_rh_inferiortemporal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness - -#age factor -agefac =~ age +rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness " -sr2_lh_frontalpole_corage <- " +sr2_rh_inferiortemporal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness - -#age factor -agefac =~ age +rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness " # And for hormone models only -hm1_lh_frontalpole_cor <- " +hm1_rh_inferiortemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8727,10 +8259,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness +rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness " -hm2_lh_frontalpole_cor <- " +hm2_rh_inferiortemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8740,46 +8272,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness +rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness " +# Fit models +fit_fm2v3_rh_inferiortemporal_cor <- cfa(fm2v3_rh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_frontalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness +fit_fm1v3_rh_inferiortemporal_cor <- cfa(fm1v3_rh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_inferiortemporal_cor <- cfa(sr1_rh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_frontalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_inferiortemporal_cor <- cfa(sr2_rh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_inferiortemporal_cor <- cfa(hm1_rh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_inferiortemporal_cor <- cfa(hm2_rh_inferiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_frontalpole_fac =~ lh_frontalpole_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_inferiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_inferiortemporal_cor, fit.measures = T, standardized = T) -####### lh_temporalpole_thickness ####### +####### rh_isthmuscingulate_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_temporalpole_cor <- " +fm2v3_rh_isthmuscingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -8807,10 +8339,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_temporalpole_fac =~ lh_temporalpole_thickness +rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness " -fm2v3_lh_temporalpole_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_isthmuscingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -8819,12 +8352,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -8836,33 +8370,107 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_temporalpole_fac =~ lh_temporalpole_thickness +#thickness factor +rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +" +# Do the same for self-report models only +sr1_rh_isthmuscingulate_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_temporalpole_cor <- " -#Latent Variables +sr2_rh_isthmuscingulate_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +" +# And for hormone models only +hm1_rh_isthmuscingulate_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +#thickness factor +rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +" -#Covariances for Saliva Sample Day +hm2_rh_isthmuscingulate_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +" +# Fit models +fit_fm2v3_rh_isthmuscingulate_cor <- cfa(fm2v3_rh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_isthmuscingulate_cor <- cfa(fm1v3_rh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_isthmuscingulate_cor <- cfa(sr1_rh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_isthmuscingulate_cor <- cfa(sr2_rh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_isthmuscingulate_cor <- cfa(hm1_rh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_isthmuscingulate_cor <- cfa(hm2_rh_isthmuscingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) + +####### rh_lateraloccipital_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_lateraloccipital_cor <- " +#Latent Variables + +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Self-Report +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr + +#Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 estr1 ~~ test1 dhea2 ~~ estr2 + test2 @@ -8872,11 +8480,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness " -fm1v3_lh_temporalpole_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_lateraloccipital_cor <- " #Latent Variables #Saliva - Level 1 @@ -8904,54 +8514,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness - -#age factor -agefac =~ age +rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness " # Do the same for self-report models only -sr1_lh_temporalpole_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness -" - -sr2_lh_temporalpole_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness -" - -sr1_lh_temporalpole_corage <- " +sr1_rh_lateraloccipital_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness - -#age factor -agefac =~ age +rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness " -sr2_lh_temporalpole_corage <- " +sr2_rh_lateraloccipital_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness - -#age factor -agefac =~ age +rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness " # And for hormone models only -hm1_lh_temporalpole_cor <- " +hm1_rh_lateraloccipital_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8961,10 +8545,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness +rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness " -hm2_lh_temporalpole_cor <- " +hm2_rh_lateraloccipital_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -8974,77 +8558,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness +rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness " +# Fit models +fit_fm2v3_rh_lateraloccipital_cor <- cfa(fm2v3_rh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_temporalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness +fit_fm1v3_rh_lateraloccipital_cor <- cfa(fm1v3_rh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_lateraloccipital_cor <- cfa(sr1_rh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_temporalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_lateraloccipital_cor <- cfa(sr2_rh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_lateraloccipital_cor <- cfa(hm1_rh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_lateraloccipital_cor <- cfa(hm2_rh_lateraloccipital_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_temporalpole_fac =~ lh_temporalpole_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_lateraloccipital_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_lateraloccipital_cor, fit.measures = T, standardized = T) -####### lh_transversetemporal_thickness ####### +####### rh_lateralorbitofrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_transversetemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_transversetemporal_fac =~ lh_transversetemporal_thickness -" - -fm2v3_lh_transversetemporal_corage <- " +fm2v3_rh_lateralorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9072,45 +8625,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_transversetemporal_fac =~ lh_transversetemporal_thickness - -#age factor -agefac =~ age +rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_transversetemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness -" - -fm1v3_lh_transversetemporal_corage <- " +fm1v3_rh_lateralorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9138,68 +8657,41 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness - -#age factor -agefac =~ age +rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness " - # Do the same for self-report models only -sr1_lh_transversetemporal_cor <- " +sr1_rh_lateralorbitofrontal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness +rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness " -sr2_lh_transversetemporal_cor <- " +sr2_rh_lateralorbitofrontal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness +rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness " -sr1_lh_transversetemporal_corage <- " +# And for hormone models only +hm1_rh_lateralorbitofrontal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + #Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 +puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -sr2_lh_transversetemporal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_lh_transversetemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness +rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness " -hm2_lh_transversetemporal_cor <- " +hm2_rh_lateralorbitofrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9209,77 +8701,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness +rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness " +# Fit models +fit_fm2v3_rh_lateralorbitofrontal_cor <- cfa(fm2v3_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_transversetemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness +fit_fm1v3_rh_lateralorbitofrontal_cor <- cfa(fm1v3_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_lateralorbitofrontal_cor <- cfa(sr1_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_transversetemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_lateralorbitofrontal_cor <- cfa(sr2_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_lateralorbitofrontal_cor <- cfa(hm1_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_lateralorbitofrontal_cor <- cfa(hm2_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_transversetemporal_fac =~ lh_transversetemporal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -####### lh_insula_thickness ####### +####### rh_lingual_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_lh_insula_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -lh_insula_fac =~ lh_insula_thickness -" - -fm2v3_lh_insula_corage <- " +fm2v3_rh_lingual_cor <- " #Latent Variables #Saliva - Level 1 @@ -9307,45 +8768,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -lh_insula_fac =~ lh_insula_thickness - -#age factor -agefac =~ age +rh_lingual_fac =~ rh_lingual_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_lh_insula_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -lh_insula_fac =~ lh_insula_thickness -" - -fm1v3_lh_insula_corage <- " +fm1v3_rh_lingual_cor <- " #Latent Variables #Saliva - Level 1 @@ -9373,54 +8800,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -lh_insula_fac =~ lh_insula_thickness - -#age factor -agefac =~ age +rh_lingual_fac =~ rh_lingual_thickness " # Do the same for self-report models only -sr1_lh_insula_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -lh_insula_fac =~ lh_insula_thickness -" - -sr2_lh_insula_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -lh_insula_fac =~ lh_insula_thickness -" - -sr1_lh_insula_corage <- " +sr1_rh_lingual_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -lh_insula_fac =~ lh_insula_thickness - -#age factor -agefac =~ age +rh_lingual_fac =~ rh_lingual_thickness " -sr2_lh_insula_corage <- " +sr2_rh_lingual_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -lh_insula_fac =~ lh_insula_thickness - -#age factor -agefac =~ age +rh_lingual_fac =~ rh_lingual_thickness " # And for hormone models only -hm1_lh_insula_cor <- " +hm1_rh_lingual_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9430,10 +8831,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -lh_insula_fac =~ lh_insula_thickness +rh_lingual_fac =~ rh_lingual_thickness " -hm2_lh_insula_cor <- " +hm2_rh_lingual_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9443,46 +8844,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -lh_insula_fac =~ lh_insula_thickness +rh_lingual_fac =~ rh_lingual_thickness " +# Fit models +fit_fm2v3_rh_lingual_cor <- cfa(fm2v3_rh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_lh_insula_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -lh_insula_fac =~ lh_insula_thickness +fit_fm1v3_rh_lingual_cor <- cfa(fm1v3_rh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_lingual_cor <- cfa(sr1_rh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_lh_insula_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_lingual_cor <- cfa(sr2_rh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_lingual_cor <- cfa(hm1_rh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_lingual_cor <- cfa(hm2_rh_lingual_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -lh_insula_fac =~ lh_insula_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_lingual_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_lingual_cor, fit.measures = T, standardized = T) -####### rh_bankssts_thickness ####### +####### rh_medialorbitofrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_bankssts_cor <- " +fm2v3_rh_medialorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9510,10 +8911,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_bankssts_fac =~ rh_bankssts_thickness +rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness " -fm2v3_rh_bankssts_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_medialorbitofrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9522,12 +8924,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -9539,16 +8942,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_bankssts_fac =~ rh_bankssts_thickness +#thickness factor +rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +" +# Do the same for self-report models only +sr1_rh_medialorbitofrontal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_bankssts_cor <- " +sr2_rh_medialorbitofrontal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +" + +# And for hormone models only +hm1_rh_medialorbitofrontal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +" + +hm2_rh_medialorbitofrontal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +" +# Fit models +fit_fm2v3_rh_medialorbitofrontal_cor <- cfa(fm2v3_rh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_medialorbitofrontal_cor <- cfa(fm1v3_rh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_medialorbitofrontal_cor <- cfa(sr1_rh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_medialorbitofrontal_cor <- cfa(sr2_rh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_medialorbitofrontal_cor <- cfa(hm1_rh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_medialorbitofrontal_cor <- cfa(hm2_rh_medialorbitofrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) + +####### rh_middletemporal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_middletemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9557,13 +9035,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -9575,11 +9052,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_middletemporal_fac =~ rh_middletemporal_thickness " -fm1v3_rh_bankssts_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_middletemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9607,55 +9086,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness - -#age factor -agefac =~ age +rh_middletemporal_fac =~ rh_middletemporal_thickness " - # Do the same for self-report models only -sr1_rh_bankssts_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness -" - -sr2_rh_bankssts_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness -" - -sr1_rh_bankssts_corage <- " +sr1_rh_middletemporal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness - -#age factor -agefac =~ age +rh_middletemporal_fac =~ rh_middletemporal_thickness " -sr2_rh_bankssts_corage <- " +sr2_rh_middletemporal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness - -#age factor -agefac =~ age +rh_middletemporal_fac =~ rh_middletemporal_thickness " # And for hormone models only -hm1_rh_bankssts_cor <- " +hm1_rh_middletemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9665,10 +9117,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness +rh_middletemporal_fac =~ rh_middletemporal_thickness " -hm2_rh_bankssts_cor <- " +hm2_rh_middletemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9678,77 +9130,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness +rh_middletemporal_fac =~ rh_middletemporal_thickness " +# Fit models +fit_fm2v3_rh_middletemporal_cor <- cfa(fm2v3_rh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_bankssts_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness +fit_fm1v3_rh_middletemporal_cor <- cfa(fm1v3_rh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_middletemporal_cor <- cfa(sr1_rh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_bankssts_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_middletemporal_cor <- cfa(sr2_rh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_middletemporal_cor <- cfa(hm1_rh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_middletemporal_cor <- cfa(hm2_rh_middletemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_bankssts_fac =~ rh_bankssts_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_middletemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_middletemporal_cor, fit.measures = T, standardized = T) -####### rh_caudalanteriorcingulate_thickness ####### +####### rh_parahippocampal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_caudalanteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness -" - -fm2v3_rh_caudalanteriorcingulate_corage <- " +fm2v3_rh_parahippocampal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9776,14 +9197,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness - -#age factor -agefac =~ age +rh_parahippocampal_fac =~ rh_parahippocampal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_caudalanteriorcingulate_cor <- " +fm1v3_rh_parahippocampal_cor <- " #Latent Variables #Saliva - Level 1 @@ -9811,86 +9229,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness +rh_parahippocampal_fac =~ rh_parahippocampal_thickness " +# Do the same for self-report models only +sr1_rh_parahippocampal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -fm1v3_rh_caudalanteriorcingulate_corage <- " -#Latent Variables +#thickness factor +rh_parahippocampal_fac =~ rh_parahippocampal_thickness +" -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_caudalanteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness -" - -sr2_rh_caudalanteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness -" - -sr1_rh_caudalanteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -sr2_rh_caudalanteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 +sr2_rh_parahippocampal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness - -#age factor -agefac =~ age +rh_parahippocampal_fac =~ rh_parahippocampal_thickness " # And for hormone models only -hm1_rh_caudalanteriorcingulate_cor <- " +hm1_rh_parahippocampal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9900,10 +9260,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness +rh_parahippocampal_fac =~ rh_parahippocampal_thickness " -hm2_rh_caudalanteriorcingulate_cor <- " +hm2_rh_parahippocampal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -9913,46 +9273,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness +rh_parahippocampal_fac =~ rh_parahippocampal_thickness " +# Fit models +fit_fm2v3_rh_parahippocampal_cor <- cfa(fm2v3_rh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_caudalanteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness +fit_fm1v3_rh_parahippocampal_cor <- cfa(fm1v3_rh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_parahippocampal_cor <- cfa(sr1_rh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_caudalanteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_parahippocampal_cor <- cfa(sr2_rh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_parahippocampal_cor <- cfa(hm1_rh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_parahippocampal_cor <- cfa(hm2_rh_parahippocampal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_caudalanteriorcingulate_fac =~ rh_caudalanteriorcingulate_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_parahippocampal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_parahippocampal_cor, fit.measures = T, standardized = T) -####### rh_caudalmiddlefrontal_thickness ####### +####### rh_paracentral_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_caudalmiddlefrontal_cor <- " +fm2v3_rh_paracentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -9980,10 +9340,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +rh_paracentral_fac =~ rh_paracentral_thickness " -fm2v3_rh_caudalmiddlefrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_paracentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -9992,12 +9353,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -10009,16 +9371,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +#thickness factor +rh_paracentral_fac =~ rh_paracentral_thickness +" +# Do the same for self-report models only +sr1_rh_paracentral_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_paracentral_fac =~ rh_paracentral_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_caudalmiddlefrontal_cor <- " +sr2_rh_paracentral_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_paracentral_fac =~ rh_paracentral_thickness +" + +# And for hormone models only +hm1_rh_paracentral_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_paracentral_fac =~ rh_paracentral_thickness +" + +hm2_rh_paracentral_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_paracentral_fac =~ rh_paracentral_thickness +" +# Fit models +fit_fm2v3_rh_paracentral_cor <- cfa(fm2v3_rh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_paracentral_cor <- cfa(fm1v3_rh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_paracentral_cor <- cfa(sr1_rh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_paracentral_cor <- cfa(sr2_rh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_paracentral_cor <- cfa(hm1_rh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_paracentral_cor <- cfa(hm2_rh_paracentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_paracentral_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_paracentral_cor, fit.measures = T, standardized = T) + +####### rh_parsopercularis_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_parsopercularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -10027,13 +9464,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -10045,11 +9481,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_parsopercularis_fac =~ rh_parsopercularis_thickness " -fm1v3_rh_caudalmiddlefrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_parsopercularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -10077,55 +9515,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness - -#age factor -agefac =~ age +rh_parsopercularis_fac =~ rh_parsopercularis_thickness " - # Do the same for self-report models only -sr1_rh_caudalmiddlefrontal_cor <- " +sr1_rh_parsopercularis_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +rh_parsopercularis_fac =~ rh_parsopercularis_thickness " -sr2_rh_caudalmiddlefrontal_cor <- " +sr2_rh_parsopercularis_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness -" - -sr1_rh_caudalmiddlefrontal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_caudalmiddlefrontal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness - -#age factor -agefac =~ age +rh_parsopercularis_fac =~ rh_parsopercularis_thickness " # And for hormone models only -hm1_rh_caudalmiddlefrontal_cor <- " +hm1_rh_parsopercularis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10135,10 +9546,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +rh_parsopercularis_fac =~ rh_parsopercularis_thickness " -hm2_rh_caudalmiddlefrontal_cor <- " +hm2_rh_parsopercularis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10148,77 +9559,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +rh_parsopercularis_fac =~ rh_parsopercularis_thickness " +# Fit models +fit_fm2v3_rh_parsopercularis_cor <- cfa(fm2v3_rh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_caudalmiddlefrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness +fit_fm1v3_rh_parsopercularis_cor <- cfa(fm1v3_rh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_parsopercularis_cor <- cfa(sr1_rh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_caudalmiddlefrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_parsopercularis_cor <- cfa(sr2_rh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_parsopercularis_cor <- cfa(hm1_rh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_parsopercularis_cor <- cfa(hm2_rh_parsopercularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_caudalmiddlefrontal_fac =~ rh_caudalmiddlefrontal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_parsopercularis_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_parsopercularis_cor, fit.measures = T, standardized = T) -####### rh_cuneus_thickness ####### +####### rh_parsorbitalis_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_cuneus_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_cuneus_fac =~ rh_cuneus_thickness -" - -fm2v3_rh_cuneus_corage <- " +fm2v3_rh_parsorbitalis_cor <- " #Latent Variables #Saliva - Level 1 @@ -10246,45 +9626,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_cuneus_fac =~ rh_cuneus_thickness - -#age factor -agefac =~ age +rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_cuneus_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness -" - -fm1v3_rh_cuneus_corage <- " +fm1v3_rh_parsorbitalis_cor <- " #Latent Variables #Saliva - Level 1 @@ -10312,55 +9658,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness - -#age factor -agefac =~ age +rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness " - # Do the same for self-report models only -sr1_rh_cuneus_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness -" - -sr2_rh_cuneus_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness -" - -sr1_rh_cuneus_corage <- " +sr1_rh_parsorbitalis_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness - -#age factor -agefac =~ age +rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness " -sr2_rh_cuneus_corage <- " +sr2_rh_parsorbitalis_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness - -#age factor -agefac =~ age +rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness " # And for hormone models only -hm1_rh_cuneus_cor <- " +hm1_rh_parsorbitalis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10370,10 +9689,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness +rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness " -hm2_rh_cuneus_cor <- " +hm2_rh_parsorbitalis_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10383,46 +9702,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness +rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness " +# Fit models +fit_fm2v3_rh_parsorbitalis_cor <- cfa(fm2v3_rh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_cuneus_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness +fit_fm1v3_rh_parsorbitalis_cor <- cfa(fm1v3_rh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_parsorbitalis_cor <- cfa(sr1_rh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_cuneus_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_parsorbitalis_cor <- cfa(sr2_rh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_parsorbitalis_cor <- cfa(hm1_rh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_parsorbitalis_cor <- cfa(hm2_rh_parsorbitalis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_cuneus_fac =~ rh_cuneus_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_parsorbitalis_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_parsorbitalis_cor, fit.measures = T, standardized = T) -####### rh_entorhinal_thickness ####### +####### rh_parstriangularis_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_entorhinal_cor <- " +fm2v3_rh_parstriangularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -10450,10 +9769,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_entorhinal_fac =~ rh_entorhinal_thickness +rh_parstriangularis_fac =~ rh_parstriangularis_thickness " -fm2v3_rh_entorhinal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_parstriangularis_cor <- " #Latent Variables #Saliva - Level 1 @@ -10462,12 +9782,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -10479,16 +9800,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_entorhinal_fac =~ rh_entorhinal_thickness +#thickness factor +rh_parstriangularis_fac =~ rh_parstriangularis_thickness +" +# Do the same for self-report models only +sr1_rh_parstriangularis_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_parstriangularis_fac =~ rh_parstriangularis_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_entorhinal_cor <- " +sr2_rh_parstriangularis_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_parstriangularis_fac =~ rh_parstriangularis_thickness +" + +# And for hormone models only +hm1_rh_parstriangularis_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_parstriangularis_fac =~ rh_parstriangularis_thickness +" + +hm2_rh_parstriangularis_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_parstriangularis_fac =~ rh_parstriangularis_thickness +" +# Fit models +fit_fm2v3_rh_parstriangularis_cor <- cfa(fm2v3_rh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_parstriangularis_cor <- cfa(fm1v3_rh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_parstriangularis_cor <- cfa(sr1_rh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_parstriangularis_cor <- cfa(sr2_rh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_parstriangularis_cor <- cfa(hm1_rh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_parstriangularis_cor <- cfa(hm2_rh_parstriangularis_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_parstriangularis_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_parstriangularis_cor, fit.measures = T, standardized = T) + +####### rh_pericalcarine_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_pericalcarine_cor <- " #Latent Variables #Saliva - Level 1 @@ -10497,13 +9893,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -10515,11 +9910,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_pericalcarine_fac =~ rh_pericalcarine_thickness " -fm1v3_rh_entorhinal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_pericalcarine_cor <- " #Latent Variables #Saliva - Level 1 @@ -10547,55 +9944,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness - -#age factor -agefac =~ age +rh_pericalcarine_fac =~ rh_pericalcarine_thickness " - # Do the same for self-report models only -sr1_rh_entorhinal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness -" - -sr2_rh_entorhinal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness -" - -sr1_rh_entorhinal_corage <- " +sr1_rh_pericalcarine_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness - -#age factor -agefac =~ age +rh_pericalcarine_fac =~ rh_pericalcarine_thickness " -sr2_rh_entorhinal_corage <- " +sr2_rh_pericalcarine_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness - -#age factor -agefac =~ age +rh_pericalcarine_fac =~ rh_pericalcarine_thickness " # And for hormone models only -hm1_rh_entorhinal_cor <- " +hm1_rh_pericalcarine_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10605,10 +9975,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness +rh_pericalcarine_fac =~ rh_pericalcarine_thickness " -hm2_rh_entorhinal_cor <- " +hm2_rh_pericalcarine_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10618,46 +9988,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness +rh_pericalcarine_fac =~ rh_pericalcarine_thickness " +# Fit models +fit_fm2v3_rh_pericalcarine_cor <- cfa(fm2v3_rh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_entorhinal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness +fit_fm1v3_rh_pericalcarine_cor <- cfa(fm1v3_rh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_pericalcarine_cor <- cfa(sr1_rh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_entorhinal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_pericalcarine_cor <- cfa(sr2_rh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_pericalcarine_cor <- cfa(hm1_rh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_pericalcarine_cor <- cfa(hm2_rh_pericalcarine_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_entorhinal_fac =~ rh_entorhinal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_pericalcarine_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_pericalcarine_cor, fit.measures = T, standardized = T) -####### rh_fusiform_thickness ####### +####### rh_postcentral_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_fusiform_cor <- " +fm2v3_rh_postcentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -10685,45 +10055,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_fusiform_fac =~ rh_fusiform_thickness +rh_postcentral_fac =~ rh_postcentral_thickness " - -fm2v3_rh_fusiform_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_fusiform_fac =~ rh_fusiform_thickness - -#age factor -agefac =~ age -" # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_fusiform_cor <- " +fm1v3_rh_postcentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -10751,86 +10087,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness +rh_postcentral_fac =~ rh_postcentral_thickness " +# Do the same for self-report models only +sr1_rh_postcentral_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -fm1v3_rh_fusiform_corage <- " -#Latent Variables +#thickness factor +rh_postcentral_fac =~ rh_postcentral_thickness +" + +sr2_rh_postcentral_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_postcentral_fac =~ rh_postcentral_thickness +" -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_fusiform_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness -" - -sr2_rh_fusiform_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness -" - -sr1_rh_fusiform_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness - -#age factor -agefac =~ age -" - -sr2_rh_fusiform_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_fusiform_cor <- " +# And for hormone models only +hm1_rh_postcentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10840,10 +10118,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness +rh_postcentral_fac =~ rh_postcentral_thickness " -hm2_rh_fusiform_cor <- " +hm2_rh_postcentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -10853,46 +10131,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness +rh_postcentral_fac =~ rh_postcentral_thickness " +# Fit models +fit_fm2v3_rh_postcentral_cor <- cfa(fm2v3_rh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_fusiform_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness +fit_fm1v3_rh_postcentral_cor <- cfa(fm1v3_rh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_postcentral_cor <- cfa(sr1_rh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_fusiform_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_postcentral_cor <- cfa(sr2_rh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_postcentral_cor <- cfa(hm1_rh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_postcentral_cor <- cfa(hm2_rh_postcentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_fusiform_fac =~ rh_fusiform_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_postcentral_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_postcentral_cor, fit.measures = T, standardized = T) -####### left inferior parietal ####### +####### rh_posteriorcingulate_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_inferiorparietal_cor <- " +fm2v3_rh_posteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -10904,7 +10182,7 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal_sr =~ PDS2 + PDS3 + PBIP2 gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 -#Neuroendocrine Systems (Saliva + Qs) - Level 3 +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 adrenal =~ sal_dhea + sal_test + adrenal_sr gonadal =~ sal_estr + gonadal_sr @@ -10920,10 +10198,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness " -fm2v3_rh_inferiorparietal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_posteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -10932,12 +10211,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#Neuroendocrine Systems (Saliva + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -10949,16 +10229,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +#thickness factor +rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness +" +# Do the same for self-report models only +sr1_rh_posteriorcingulate_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_inferiorparietal_cor <- " +sr2_rh_posteriorcingulate_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness +" + +# And for hormone models only +hm1_rh_posteriorcingulate_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness +" + +hm2_rh_posteriorcingulate_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness +" +# Fit models +fit_fm2v3_rh_posteriorcingulate_cor <- cfa(fm2v3_rh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_posteriorcingulate_cor <- cfa(fm1v3_rh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_posteriorcingulate_cor <- cfa(sr1_rh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_posteriorcingulate_cor <- cfa(sr2_rh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_posteriorcingulate_cor <- cfa(hm1_rh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_posteriorcingulate_cor <- cfa(hm2_rh_posteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) + +####### rh_precentral_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_precentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -10967,13 +10322,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -10985,11 +10339,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_precentral_fac =~ rh_precentral_thickness " -fm1v3_rh_inferiorparietal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_precentral_cor <- " #Latent Variables #Saliva - Level 1 @@ -11017,55 +10373,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness - -#age factor -agefac =~ age +rh_precentral_fac =~ rh_precentral_thickness " - # Do the same for self-report models only -sr1_rh_inferiorparietal_cor <- " +sr1_rh_precentral_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness -" - -sr2_rh_inferiorparietal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness -" - -sr1_rh_inferiorparietal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness - -#age factor -agefac =~ age +rh_precentral_fac =~ rh_precentral_thickness " -sr2_rh_inferiorparietal_corage <- " +sr2_rh_precentral_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness - -#age factor -agefac =~ age +rh_precentral_fac =~ rh_precentral_thickness " # And for hormone models only -hm1_rh_inferiorparietal_cor <- " +hm1_rh_precentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11075,10 +10404,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +rh_precentral_fac =~ rh_precentral_thickness " -hm2_rh_inferiorparietal_cor <- " +hm2_rh_precentral_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11088,77 +10417,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +rh_precentral_fac =~ rh_precentral_thickness " +# Fit models +fit_fm2v3_rh_precentral_cor <- cfa(fm2v3_rh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_inferiorparietal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness +fit_fm1v3_rh_precentral_cor <- cfa(fm1v3_rh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_precentral_cor <- cfa(sr1_rh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_inferiorparietal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_precentral_cor <- cfa(sr2_rh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_precentral_cor <- cfa(hm1_rh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_precentral_cor <- cfa(hm2_rh_precentral_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_inferiorparietal_fac =~ rh_inferiorparietal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_precentral_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_precentral_cor, fit.measures = T, standardized = T) -####### rh_inferiortemporal_thickness ####### +####### rh_precuneus_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_inferiortemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness -" - -fm2v3_rh_inferiortemporal_corage <- " +fm2v3_rh_precuneus_cor <- " #Latent Variables #Saliva - Level 1 @@ -11186,45 +10484,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness - -#age factor -agefac =~ age +rh_precuneus_fac =~ rh_precuneus_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_inferiortemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness -" - -fm1v3_rh_inferiortemporal_corage <- " +fm1v3_rh_precuneus_cor <- " #Latent Variables #Saliva - Level 1 @@ -11252,55 +10516,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness - -#age factor -agefac =~ age +rh_precuneus_fac =~ rh_precuneus_thickness " - # Do the same for self-report models only -sr1_rh_inferiortemporal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness -" - -sr2_rh_inferiortemporal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness -" - -sr1_rh_inferiortemporal_corage <- " +sr1_rh_precuneus_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness - -#age factor -agefac =~ age +rh_precuneus_fac =~ rh_precuneus_thickness " -sr2_rh_inferiortemporal_corage <- " +sr2_rh_precuneus_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness - -#age factor -agefac =~ age +rh_precuneus_fac =~ rh_precuneus_thickness " # And for hormone models only -hm1_rh_inferiortemporal_cor <- " +hm1_rh_precuneus_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11310,10 +10547,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness +rh_precuneus_fac =~ rh_precuneus_thickness " -hm2_rh_inferiortemporal_cor <- " +hm2_rh_precuneus_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11323,46 +10560,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness +rh_precuneus_fac =~ rh_precuneus_thickness " +# Fit models +fit_fm2v3_rh_precuneus_cor <- cfa(fm2v3_rh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_inferiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness +fit_fm1v3_rh_precuneus_cor <- cfa(fm1v3_rh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_precuneus_cor <- cfa(sr1_rh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_inferiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_precuneus_cor <- cfa(sr2_rh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_precuneus_cor <- cfa(hm1_rh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_precuneus_cor <- cfa(hm2_rh_precuneus_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_inferiortemporal_fac =~ rh_inferiortemporal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_precuneus_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_precuneus_cor, fit.measures = T, standardized = T) -####### rh_isthmuscingulate_thickness ####### +####### rh_rostralanteriorcingulate_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_isthmuscingulate_cor <- " +fm2v3_rh_rostralanteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -11390,10 +10627,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness " -fm2v3_rh_isthmuscingulate_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_rostralanteriorcingulate_cor <- " #Latent Variables #Saliva - Level 1 @@ -11402,12 +10640,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -11419,16 +10658,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +#thickness factor +rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness +" +# Do the same for self-report models only +sr1_rh_rostralanteriorcingulate_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_isthmuscingulate_cor <- " +sr2_rh_rostralanteriorcingulate_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness +" + +# And for hormone models only +hm1_rh_rostralanteriorcingulate_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness +" + +hm2_rh_rostralanteriorcingulate_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness +" +# Fit models +fit_fm2v3_rh_rostralanteriorcingulate_cor <- cfa(fm2v3_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_rostralanteriorcingulate_cor <- cfa(fm1v3_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_rostralanteriorcingulate_cor <- cfa(sr1_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_rostralanteriorcingulate_cor <- cfa(sr2_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_rostralanteriorcingulate_cor <- cfa(hm1_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_rostralanteriorcingulate_cor <- cfa(hm2_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) + +####### rh_rostralmiddlefrontal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_rostralmiddlefrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11437,13 +10751,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -11455,11 +10768,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness " -fm1v3_rh_isthmuscingulate_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_rostralmiddlefrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11487,55 +10802,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness - -#age factor -agefac =~ age +rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness " - # Do the same for self-report models only -sr1_rh_isthmuscingulate_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness -" - -sr2_rh_isthmuscingulate_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness -" - -sr1_rh_isthmuscingulate_corage <- " +sr1_rh_rostralmiddlefrontal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness - -#age factor -agefac =~ age +rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness " -sr2_rh_isthmuscingulate_corage <- " +sr2_rh_rostralmiddlefrontal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness - -#age factor -agefac =~ age +rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness " # And for hormone models only -hm1_rh_isthmuscingulate_cor <- " +hm1_rh_rostralmiddlefrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11545,10 +10833,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness " -hm2_rh_isthmuscingulate_cor <- " +hm2_rh_rostralmiddlefrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11558,46 +10846,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness " +# Fit models +fit_fm2v3_rh_rostralmiddlefrontal_cor <- cfa(fm2v3_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_isthmuscingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness +fit_fm1v3_rh_rostralmiddlefrontal_cor <- cfa(fm1v3_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_rostralmiddlefrontal_cor <- cfa(sr1_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_isthmuscingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_rostralmiddlefrontal_cor <- cfa(sr2_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_rostralmiddlefrontal_cor <- cfa(hm1_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_rostralmiddlefrontal_cor <- cfa(hm2_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_isthmuscingulate_fac =~ rh_isthmuscingulate_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -####### rh_lateraloccipital_thickness ####### +####### rh_superiorfrontal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_lateraloccipital_cor <- " +fm2v3_rh_superiorfrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11625,10 +10913,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness +rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness " -fm2v3_rh_lateraloccipital_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_superiorfrontal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11637,12 +10926,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -11654,32 +10944,105 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness +#thickness factor +rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness +" +# Do the same for self-report models only +sr1_rh_superiorfrontal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness " +sr2_rh_superiorfrontal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_lateraloccipital_cor <- " -#Latent Variables +#thickness factor +rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness +" +# And for hormone models only +hm1_rh_superiorfrontal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +#thickness factor +rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness +" + +hm2_rh_superiorfrontal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness +" +# Fit models +fit_fm2v3_rh_superiorfrontal_cor <- cfa(fm2v3_rh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_superiorfrontal_cor <- cfa(fm1v3_rh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_superiorfrontal_cor <- cfa(sr1_rh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_superiorfrontal_cor <- cfa(sr2_rh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_superiorfrontal_cor <- cfa(hm1_rh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_superiorfrontal_cor <- cfa(hm2_rh_superiorfrontal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_superiorfrontal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_superiorfrontal_cor, fit.measures = T, standardized = T) + +####### rh_superiorparietal_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_superiorparietal_cor <- " +#Latent Variables + +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Self-Report +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -11691,11 +11054,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_superiorparietal_fac =~ rh_superiorparietal_thickness " -fm1v3_rh_lateraloccipital_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_superiorparietal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11723,55 +11088,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness - -#age factor -agefac =~ age +rh_superiorparietal_fac =~ rh_superiorparietal_thickness " - # Do the same for self-report models only -sr1_rh_lateraloccipital_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness -" - -sr2_rh_lateraloccipital_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness -" - -sr1_rh_lateraloccipital_corage <- " +sr1_rh_superiorparietal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness - -#age factor -agefac =~ age +rh_superiorparietal_fac =~ rh_superiorparietal_thickness " -sr2_rh_lateraloccipital_corage <- " +sr2_rh_superiorparietal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness - -#age factor -agefac =~ age +rh_superiorparietal_fac =~ rh_superiorparietal_thickness " # And for hormone models only -hm1_rh_lateraloccipital_cor <- " +hm1_rh_superiorparietal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11781,10 +11119,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness +rh_superiorparietal_fac =~ rh_superiorparietal_thickness " -hm2_rh_lateraloccipital_cor <- " +hm2_rh_superiorparietal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -11794,77 +11132,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness +rh_superiorparietal_fac =~ rh_superiorparietal_thickness " +# Fit models +fit_fm2v3_rh_superiorparietal_cor <- cfa(fm2v3_rh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_lateraloccipital_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness +fit_fm1v3_rh_superiorparietal_cor <- cfa(fm1v3_rh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_superiorparietal_cor <- cfa(sr1_rh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_lateraloccipital_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_superiorparietal_cor <- cfa(sr2_rh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_superiorparietal_cor <- cfa(hm1_rh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_superiorparietal_cor <- cfa(hm2_rh_superiorparietal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_lateraloccipital_fac =~ rh_lateraloccipital_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_superiorparietal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_superiorparietal_cor, fit.measures = T, standardized = T) -####### rh_lateralorbitofrontal_thickness ####### +####### rh_superiortemporal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_lateralorbitofrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness -" - -fm2v3_rh_lateralorbitofrontal_corage <- " +fm2v3_rh_superiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11892,45 +11199,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age +rh_superiortemporal_fac =~ rh_superiortemporal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_lateralorbitofrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness -" - -fm1v3_rh_lateralorbitofrontal_corage <- " +fm1v3_rh_superiortemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -11958,68 +11231,41 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age +rh_superiortemporal_fac =~ rh_superiortemporal_thickness " - # Do the same for self-report models only -sr1_rh_lateralorbitofrontal_cor <- " +sr1_rh_superiortemporal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness +rh_superiortemporal_fac =~ rh_superiortemporal_thickness " -sr2_rh_lateralorbitofrontal_cor <- " +sr2_rh_superiortemporal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness +rh_superiortemporal_fac =~ rh_superiortemporal_thickness " -sr1_rh_lateralorbitofrontal_corage <- " +# And for hormone models only +hm1_rh_superiortemporal_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + #Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 +puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_lateralorbitofrontal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_lateralorbitofrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness +rh_superiortemporal_fac =~ rh_superiortemporal_thickness " -hm2_rh_lateralorbitofrontal_cor <- " +hm2_rh_superiortemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -12029,77 +11275,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness +rh_superiortemporal_fac =~ rh_superiortemporal_thickness " +# Fit models +fit_fm2v3_rh_superiortemporal_cor <- cfa(fm2v3_rh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_lateralorbitofrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness +fit_fm1v3_rh_superiortemporal_cor <- cfa(fm1v3_rh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_superiortemporal_cor <- cfa(sr1_rh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_lateralorbitofrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_superiortemporal_cor <- cfa(sr2_rh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_superiortemporal_cor <- cfa(hm1_rh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_superiortemporal_cor <- cfa(hm2_rh_superiortemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_lateralorbitofrontal_fac =~ rh_lateralorbitofrontal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_superiortemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_superiortemporal_cor, fit.measures = T, standardized = T) -####### rh_lingual_thickness ####### +####### rh_supramarginal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_lingual_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_lingual_fac =~ rh_lingual_thickness -" - -fm2v3_rh_lingual_corage <- " +fm2v3_rh_supramarginal_cor <- " #Latent Variables #Saliva - Level 1 @@ -12127,45 +11342,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_lingual_fac =~ rh_lingual_thickness - -#age factor -agefac =~ age +rh_supramarginal_fac =~ rh_supramarginal_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_lingual_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_lingual_fac =~ rh_lingual_thickness -" - -fm1v3_rh_lingual_corage <- " +fm1v3_rh_supramarginal_cor <- " #Latent Variables #Saliva - Level 1 @@ -12193,55 +11374,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_lingual_fac =~ rh_lingual_thickness - -#age factor -agefac =~ age +rh_supramarginal_fac =~ rh_supramarginal_thickness " - # Do the same for self-report models only -sr1_rh_lingual_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_lingual_fac =~ rh_lingual_thickness -" - -sr2_rh_lingual_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_lingual_fac =~ rh_lingual_thickness -" - -sr1_rh_lingual_corage <- " +sr1_rh_supramarginal_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_lingual_fac =~ rh_lingual_thickness - -#age factor -agefac =~ age +rh_supramarginal_fac =~ rh_supramarginal_thickness " -sr2_rh_lingual_corage <- " +sr2_rh_supramarginal_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_lingual_fac =~ rh_lingual_thickness - -#age factor -agefac =~ age +rh_supramarginal_fac =~ rh_supramarginal_thickness " # And for hormone models only -hm1_rh_lingual_cor <- " +hm1_rh_supramarginal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -12251,10 +11405,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_lingual_fac =~ rh_lingual_thickness +rh_supramarginal_fac =~ rh_supramarginal_thickness " -hm2_rh_lingual_cor <- " +hm2_rh_supramarginal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -12264,46 +11418,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_lingual_fac =~ rh_lingual_thickness +rh_supramarginal_fac =~ rh_supramarginal_thickness " +# Fit models +fit_fm2v3_rh_supramarginal_cor <- cfa(fm2v3_rh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_lingual_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_lingual_fac =~ rh_lingual_thickness +fit_fm1v3_rh_supramarginal_cor <- cfa(fm1v3_rh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_supramarginal_cor <- cfa(sr1_rh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_lingual_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_supramarginal_cor <- cfa(sr2_rh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_supramarginal_cor <- cfa(hm1_rh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_supramarginal_cor <- cfa(hm2_rh_supramarginal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_lingual_fac =~ rh_lingual_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_supramarginal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_supramarginal_cor, fit.measures = T, standardized = T) -####### rh_medialorbitofrontal_thickness ####### +####### rh_frontalpole_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_medialorbitofrontal_cor <- " +fm2v3_rh_frontalpole_cor <- " #Latent Variables #Saliva - Level 1 @@ -12331,10 +11485,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +rh_frontalpole_fac =~ rh_frontalpole_thickness " -fm2v3_rh_medialorbitofrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_frontalpole_cor <- " #Latent Variables #Saliva - Level 1 @@ -12343,12 +11498,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test + +#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -12360,16 +11516,91 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +#thickness factor +rh_frontalpole_fac =~ rh_frontalpole_thickness +" +# Do the same for self-report models only +sr1_rh_frontalpole_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_frontalpole_fac =~ rh_frontalpole_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_medialorbitofrontal_cor <- " +sr2_rh_frontalpole_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_frontalpole_fac =~ rh_frontalpole_thickness +" + +# And for hormone models only +hm1_rh_frontalpole_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test + +#thickness factor +rh_frontalpole_fac =~ rh_frontalpole_thickness +" + +hm2_rh_frontalpole_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + +#Latent Neuroendocrine Systems +adrenal =~ sal_dhea + sal_test + +#thickness factor +rh_frontalpole_fac =~ rh_frontalpole_thickness +" +# Fit models +fit_fm2v3_rh_frontalpole_cor <- cfa(fm2v3_rh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_fm1v3_rh_frontalpole_cor <- cfa(fm1v3_rh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr1_rh_frontalpole_cor <- cfa(sr1_rh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_sr2_rh_frontalpole_cor <- cfa(sr2_rh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_frontalpole_cor <- cfa(hm1_rh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + +fit_hm2_rh_frontalpole_cor <- cfa(hm2_rh_frontalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) + + +# Summary Stats for models +summary(fit_fm2v3_rh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_frontalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_frontalpole_cor, fit.measures = T, standardized = T) + +####### rh_temporalpole_thickness ####### + +# Now build the first one, ADR and GON correlate with thickness +# (note that lavaan automatically shows correlations for ADR and GON and thickness) +fm2v3_rh_temporalpole_cor <- " #Latent Variables #Saliva - Level 1 @@ -12378,13 +11609,12 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +adrenal_sr =~ PDS2 + PDS3 + PBIP2 +gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +adrenal =~ sal_dhea + sal_test + adrenal_sr +gonadal =~ sal_estr + gonadal_sr #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -12396,11 +11626,13 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +#covary observed l_infpar and latent neuroendo systems by tricking lavaan +# (remember that lavaan always fixes the first loading to 1) +rh_temporalpole_fac =~ rh_temporalpole_thickness " -fm1v3_rh_medialorbitofrontal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_temporalpole_cor <- " #Latent Variables #Saliva - Level 1 @@ -12428,55 +11660,28 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness - -#age factor -agefac =~ age +rh_temporalpole_fac =~ rh_temporalpole_thickness " - # Do the same for self-report models only -sr1_rh_medialorbitofrontal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness -" - -sr2_rh_medialorbitofrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness -" - -sr1_rh_medialorbitofrontal_corage <- " +sr1_rh_temporalpole_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness - -#age factor -agefac =~ age +rh_temporalpole_fac =~ rh_temporalpole_thickness " -sr2_rh_medialorbitofrontal_corage <- " +sr2_rh_temporalpole_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness - -#age factor -agefac =~ age +rh_temporalpole_fac =~ rh_temporalpole_thickness " # And for hormone models only -hm1_rh_medialorbitofrontal_cor <- " +hm1_rh_temporalpole_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -12486,10 +11691,10 @@ sal_test =~ test1 + test2 + test3 + test4 puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +rh_temporalpole_fac =~ rh_temporalpole_thickness " -hm2_rh_medialorbitofrontal_cor <- " +hm2_rh_temporalpole_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -12499,46 +11704,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +rh_temporalpole_fac =~ rh_temporalpole_thickness " +# Fit models +fit_fm2v3_rh_temporalpole_cor <- cfa(fm2v3_rh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_medialorbitofrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness +fit_fm1v3_rh_temporalpole_cor <- cfa(fm1v3_rh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr1_rh_temporalpole_cor <- cfa(sr1_rh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_medialorbitofrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_sr2_rh_temporalpole_cor <- cfa(sr2_rh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_temporalpole_cor <- cfa(hm1_rh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test +fit_hm2_rh_temporalpole_cor <- cfa(hm2_rh_temporalpole_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_medialorbitofrontal_fac =~ rh_medialorbitofrontal_thickness -#age factor -agefac =~ age -" +# Summary Stats for models +summary(fit_fm2v3_rh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_temporalpole_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_temporalpole_cor, fit.measures = T, standardized = T) -####### rh_middletemporal_thickness ####### +####### rh_transversetemporal_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_middletemporal_cor <- " +fm2v3_rh_transversetemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -12566,10 +11771,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_middletemporal_fac =~ rh_middletemporal_thickness +rh_transversetemporal_fac =~ rh_transversetemporal_thickness " -fm2v3_rh_middletemporal_corage <- " +# Check the thickness correlation with the one factor PUB latent variable, too +fm1v3_rh_transversetemporal_cor <- " #Latent Variables #Saliva - Level 1 @@ -12578,12 +11784,13 @@ sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 #Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 +pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 + +#BioVars +pub_bio =~ sal_dhea + sal_estr + sal_test #Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr +puberty =~ pub_sr + pub_bio #Covariances for Saliva Sample Day dhea1 ~~ estr1 + test1 @@ -12595,135 +11802,42 @@ estr3 ~~ test3 dhea4 ~~ estr4 + test4 estr4 ~~ test4 -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_middletemporal_fac =~ rh_middletemporal_thickness +#thickness factor +rh_transversetemporal_fac =~ rh_transversetemporal_thickness +" +# Do the same for self-report models only +sr1_rh_transversetemporal_cor <- " +#Latent Neuroendocrine Systems +puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 -#age factor -agefac =~ age +#thickness factor +rh_transversetemporal_fac =~ rh_transversetemporal_thickness " -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_middletemporal_cor <- " -#Latent Variables +sr2_rh_transversetemporal_cor <- " +#Latent Neuroendocrine Systems +adrenal =~ PDS2 + PDS3 + PBIP2 +gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 + +#thickness factor +rh_transversetemporal_fac =~ rh_transversetemporal_thickness +" +# And for hormone models only +hm1_rh_transversetemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 sal_test =~ test1 + test2 + test3 + test4 -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test +#Latent Neuroendocrine Systems +puberty =~ sal_dhea + sal_estr + sal_test -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio +#thickness factor +rh_transversetemporal_fac =~ rh_transversetemporal_thickness +" -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness -" - -fm1v3_rh_middletemporal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_middletemporal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness -" - -sr2_rh_middletemporal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness -" - -sr1_rh_middletemporal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_middletemporal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness - -#age factor -agefac =~ age -" -# And for hormone models only -hm1_rh_middletemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness -" - -hm2_rh_middletemporal_cor <- " +hm2_rh_transversetemporal_cor <- " #Saliva - Level 1 sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 sal_estr =~ estr1 + estr2 + estr3 + estr4 @@ -12733,76 +11847,46 @@ sal_test =~ test1 + test2 + test3 + test4 adrenal =~ sal_dhea + sal_test #thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness +rh_transversetemporal_fac =~ rh_transversetemporal_thickness " +# Fit models +fit_fm2v3_rh_transversetemporal_cor <- cfa(fm2v3_rh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm1_rh_middletemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test +fit_fm1v3_rh_transversetemporal_cor <- cfa(fm1v3_rh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness +fit_sr1_rh_transversetemporal_cor <- cfa(sr1_rh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr2_rh_transversetemporal_cor <- cfa(sr2_rh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_transversetemporal_cor <- cfa(hm1_rh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -hm2_rh_middletemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_hm2_rh_transversetemporal_cor <- cfa(hm2_rh_transversetemporal_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test -#thickness factor -rh_middletemporal_fac =~ rh_middletemporal_thickness +# Summary Stats for models +summary(fit_fm2v3_rh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_fm1v3_rh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr1_rh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_sr2_rh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm1_rh_transversetemporal_cor, fit.measures = T, standardized = T) +summary(fit_hm2_rh_transversetemporal_cor, fit.measures = T, standardized = T) -#age factor -agefac =~ age -" -####### rh_parahippocampal_thickness ####### +####### rh_insula_thickness ####### # Now build the first one, ADR and GON correlate with thickness # (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_parahippocampal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parahippocampal_fac =~ rh_parahippocampal_thickness -" - -fm2v3_rh_parahippocampal_corage <- " +fm2v3_rh_insula_cor <- " #Latent Variables #Saliva - Level 1 @@ -12830,45 +11914,11 @@ estr4 ~~ test4 #covary observed l_infpar and latent neuroendo systems by tricking lavaan # (remember that lavaan always fixes the first loading to 1) -rh_parahippocampal_fac =~ rh_parahippocampal_thickness - -#age factor -agefac =~ age +rh_insula_fac =~ rh_insula_thickness " # Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_parahippocampal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness -" - -fm1v3_rh_parahippocampal_corage <- " +fm1v3_rh_insula_cor <- " #Latent Variables #Saliva - Level 1 @@ -12896,7431 +11946,78 @@ dhea4 ~~ estr4 + test4 estr4 ~~ test4 #thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness - -#age factor -agefac =~ age +rh_insula_fac =~ rh_insula_thickness " - # Do the same for self-report models only -sr1_rh_parahippocampal_cor <- " +sr1_rh_insula_cor <- " #Latent Neuroendocrine Systems puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 #thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness +rh_insula_fac =~ rh_insula_thickness " -sr2_rh_parahippocampal_cor <- " +sr2_rh_insula_cor <- " #Latent Neuroendocrine Systems adrenal =~ PDS2 + PDS3 + PBIP2 gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 #thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness +rh_insula_fac =~ rh_insula_thickness " -sr1_rh_parahippocampal_corage <- " +# And for hormone models only +hm1_rh_insula_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 + #Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 +puberty =~ sal_dhea + sal_estr + sal_test #thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness - -#age factor -agefac =~ age +rh_insula_fac =~ rh_insula_thickness " - -sr2_rh_parahippocampal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_parahippocampal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness -" - -hm2_rh_parahippocampal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness -" - -hm1_rh_parahippocampal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_parahippocampal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 + +hm2_rh_insula_cor <- " +#Saliva - Level 1 +sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 +sal_estr =~ estr1 + estr2 + estr3 + estr4 +sal_test =~ test1 + test2 + test3 + test4 #Latent Neuroendocrine Systems adrenal =~ sal_dhea + sal_test #thickness factor -rh_parahippocampal_fac =~ rh_parahippocampal_thickness - -#age factor -agefac =~ age -" -####### rh_paracentral_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_paracentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_paracentral_fac =~ rh_paracentral_thickness -" - -fm2v3_rh_paracentral_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_paracentral_fac =~ rh_paracentral_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_paracentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness -" - -fm1v3_rh_paracentral_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness - -#age factor -agefac =~ age -" -# Do the same for self-report models only -sr1_rh_paracentral_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness -" - -sr2_rh_paracentral_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness -" - -sr1_rh_paracentral_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness - -#age factor -agefac =~ age +rh_insula_fac =~ rh_insula_thickness " +# Fit models +fit_fm2v3_rh_insula_cor <- cfa(fm2v3_rh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -sr2_rh_paracentral_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 +fit_fm1v3_rh_insula_cor <- cfa(fm1v3_rh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness +fit_sr1_rh_insula_cor <- cfa(sr1_rh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#age factor -agefac =~ age -" +fit_sr2_rh_insula_cor <- cfa(sr2_rh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) +fit_hm1_rh_insula_cor <- cfa(hm1_rh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -# And for hormone models only -hm1_rh_paracentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 +fit_hm2_rh_insula_cor <- cfa(hm2_rh_insula_cor, data = data, estimator = "ML", + missing = "ML", verbose = T, + ) -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness -" - -hm2_rh_paracentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness -" - -hm1_rh_paracentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness - -#age factor -agefac =~ age -" - -hm2_rh_paracentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_paracentral_fac =~ rh_paracentral_thickness - -#age factor -agefac =~ age -" -####### rh_parsopercularis_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_parsopercularis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parsopercularis_fac =~ rh_parsopercularis_thickness -" - -fm2v3_rh_parsopercularis_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parsopercularis_fac =~ rh_parsopercularis_thickness - -#age factor -agefac =~ age -" -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_parsopercularis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness -" - -fm1v3_rh_parsopercularis_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness - -#age factor -agefac =~ age -" -# Do the same for self-report models only -sr1_rh_parsopercularis_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness -" - -sr2_rh_parsopercularis_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness -" - -sr1_rh_parsopercularis_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness - -#age factor -agefac =~ age -" - -sr2_rh_parsopercularis_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness - -#age factor -agefac =~ age -" -# And for hormone models only -hm1_rh_parsopercularis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness -" - -hm2_rh_parsopercularis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness -" - -hm1_rh_parsopercularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness - -#age factor -agefac =~ age -" - -hm2_rh_parsopercularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parsopercularis_fac =~ rh_parsopercularis_thickness - -#age factor -agefac =~ age -" - -####### rh_parsorbitalis_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_parsorbitalis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness -" - -fm2v3_rh_parsorbitalis_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_parsorbitalis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness -" - -fm1v3_rh_parsorbitalis_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_parsorbitalis_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness -" - -sr2_rh_parsorbitalis_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness -" - -sr1_rh_parsorbitalis_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -sr2_rh_parsorbitalis_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_parsorbitalis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness -" - -hm2_rh_parsorbitalis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness -" - -hm1_rh_parsorbitalis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -hm2_rh_parsorbitalis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parsorbitalis_fac =~ rh_parsorbitalis_thickness - -#age factor -agefac =~ age -" - -####### rh_parstriangularis_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_parstriangularis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parstriangularis_fac =~ rh_parstriangularis_thickness -" - -fm2v3_rh_parstriangularis_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_parstriangularis_fac =~ rh_parstriangularis_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_parstriangularis_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness -" - -fm1v3_rh_parstriangularis_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_parstriangularis_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness -" - -sr2_rh_parstriangularis_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness -" - -sr1_rh_parstriangularis_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness - -#age factor -agefac =~ age -" - -sr2_rh_parstriangularis_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_parstriangularis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness -" - -hm2_rh_parstriangularis_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness -" - -hm1_rh_parstriangularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness - -#age factor -agefac =~ age -" - -hm2_rh_parstriangularis_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_parstriangularis_fac =~ rh_parstriangularis_thickness - -#age factor -agefac =~ age -" - -####### rh_pericalcarine_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_pericalcarine_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_pericalcarine_fac =~ rh_pericalcarine_thickness -" - -fm2v3_rh_pericalcarine_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_pericalcarine_fac =~ rh_pericalcarine_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_pericalcarine_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness -" - -fm1v3_rh_pericalcarine_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_pericalcarine_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness -" - -sr2_rh_pericalcarine_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness -" - -sr1_rh_pericalcarine_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness - -#age factor -agefac =~ age -" - -sr2_rh_pericalcarine_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_pericalcarine_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness -" - -hm2_rh_pericalcarine_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness -" - -hm1_rh_pericalcarine_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness - -#age factor -agefac =~ age -" - -hm2_rh_pericalcarine_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_pericalcarine_fac =~ rh_pericalcarine_thickness - -#age factor -agefac =~ age -" - -####### rh_postcentral_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_postcentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_postcentral_fac =~ rh_postcentral_thickness -" - -fm2v3_rh_postcentral_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_postcentral_fac =~ rh_postcentral_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_postcentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness -" - -fm1v3_rh_postcentral_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_postcentral_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness -" - -sr2_rh_postcentral_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness -" - -sr1_rh_postcentral_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness - -#age factor -agefac =~ age -" - -sr2_rh_postcentral_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_postcentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness -" - -hm2_rh_postcentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness -" - -hm1_rh_postcentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness - -#age factor -agefac =~ age -" - -hm2_rh_postcentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_postcentral_fac =~ rh_postcentral_thickness - -#age factor -agefac =~ age -" - -####### rh_posteriorcingulate_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_posteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness -" - -fm2v3_rh_posteriorcingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_posteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness -" - -fm1v3_rh_posteriorcingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_posteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness -" - -sr2_rh_posteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness -" - -sr1_rh_posteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness - -#age factor -agefac =~ age -" - -sr2_rh_posteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_posteriorcingulate_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness -" - -hm2_rh_posteriorcingulate_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness -" - -hm1_rh_posteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness - -#age factor -agefac =~ age -" - -hm2_rh_posteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_posteriorcingulate_fac =~ rh_posteriorcingulate_thickness - -#age factor -agefac =~ age -" - -####### rh_precentral_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_precentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_precentral_fac =~ rh_precentral_thickness -" - -fm2v3_rh_precentral_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_precentral_fac =~ rh_precentral_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_precentral_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness -" - -fm1v3_rh_precentral_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_precentral_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness -" - -sr2_rh_precentral_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness -" - -sr1_rh_precentral_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness - -#age factor -agefac =~ age -" - -sr2_rh_precentral_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_precentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness -" - -hm2_rh_precentral_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness -" - -hm1_rh_precentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness - -#age factor -agefac =~ age -" - -hm2_rh_precentral_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_precentral_fac =~ rh_precentral_thickness - -#age factor -agefac =~ age -" -####### rh_precuneus_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_precuneus_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_precuneus_fac =~ rh_precuneus_thickness -" - -fm2v3_rh_precuneus_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_precuneus_fac =~ rh_precuneus_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_precuneus_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness -" - -fm1v3_rh_precuneus_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness - -#age factor -agefac =~ age -" -# Do the same for self-report models only -sr1_rh_precuneus_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness -" - -sr2_rh_precuneus_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness -" - -sr1_rh_precuneus_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness - -#age factor -agefac =~ age -" - -sr2_rh_precuneus_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_precuneus_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness -" - -hm2_rh_precuneus_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness -" - -hm1_rh_precuneus_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness - -#age factor -agefac =~ age -" - -hm2_rh_precuneus_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_precuneus_fac =~ rh_precuneus_thickness - -#age factor -agefac =~ age -" - -####### rh_rostralanteriorcingulate_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_rostralanteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness -" - -fm2v3_rh_rostralanteriorcingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_rostralanteriorcingulate_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness -" - -fm1v3_rh_rostralanteriorcingulate_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" -# Do the same for self-report models only -sr1_rh_rostralanteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness -" - -sr2_rh_rostralanteriorcingulate_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness -" - -sr1_rh_rostralanteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -sr2_rh_rostralanteriorcingulate_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_rostralanteriorcingulate_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness -" - -hm2_rh_rostralanteriorcingulate_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness -" - -hm1_rh_rostralanteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -hm2_rh_rostralanteriorcingulate_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_rostralanteriorcingulate_fac =~ rh_rostralanteriorcingulate_thickness - -#age factor -agefac =~ age -" - -####### rh_rostralmiddlefrontal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_rostralmiddlefrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness -" - -fm2v3_rh_rostralmiddlefrontal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_rostralmiddlefrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness -" - -fm1v3_rh_rostralmiddlefrontal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_rostralmiddlefrontal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness -" - -sr2_rh_rostralmiddlefrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness -" - -sr1_rh_rostralmiddlefrontal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_rostralmiddlefrontal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_rostralmiddlefrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness -" - -hm2_rh_rostralmiddlefrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness -" - -hm1_rh_rostralmiddlefrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_rostralmiddlefrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_rostralmiddlefrontal_fac =~ rh_rostralmiddlefrontal_thickness - -#age factor -agefac =~ age -" - -####### rh_superiorfrontal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_superiorfrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness -" - -fm2v3_rh_superiorfrontal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_superiorfrontal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness -" - -fm1v3_rh_superiorfrontal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_superiorfrontal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness -" - -sr2_rh_superiorfrontal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness -" - -sr1_rh_superiorfrontal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_superiorfrontal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_superiorfrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness -" - -hm2_rh_superiorfrontal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness -" - -hm1_rh_superiorfrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_superiorfrontal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_superiorfrontal_fac =~ rh_superiorfrontal_thickness - -#age factor -agefac =~ age -" - -####### rh_superiorparietal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_superiorparietal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_superiorparietal_fac =~ rh_superiorparietal_thickness -" - -fm2v3_rh_superiorparietal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_superiorparietal_fac =~ rh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_superiorparietal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness -" - -fm1v3_rh_superiorparietal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_superiorparietal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness -" - -sr2_rh_superiorparietal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness -" - -sr1_rh_superiorparietal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_superiorparietal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_superiorparietal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness -" - -hm2_rh_superiorparietal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness -" - -hm1_rh_superiorparietal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_superiorparietal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_superiorparietal_fac =~ rh_superiorparietal_thickness - -#age factor -agefac =~ age -" - -####### rh_superiortemporal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_superiortemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_superiortemporal_fac =~ rh_superiortemporal_thickness -" - -fm2v3_rh_superiortemporal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_superiortemporal_fac =~ rh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_superiortemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness -" - -fm1v3_rh_superiortemporal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_superiortemporal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness -" - -sr2_rh_superiortemporal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness -" - -sr1_rh_superiortemporal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_superiortemporal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_superiortemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness -" - -hm2_rh_superiortemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness -" - -hm1_rh_superiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_superiortemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_superiortemporal_fac =~ rh_superiortemporal_thickness - -#age factor -agefac =~ age -" - -####### rh_supramarginal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_supramarginal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_supramarginal_fac =~ rh_supramarginal_thickness -" - -fm2v3_rh_supramarginal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_supramarginal_fac =~ rh_supramarginal_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_supramarginal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness -" - -fm1v3_rh_supramarginal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness - -#age factor -agefac =~ age -" -# Do the same for self-report models only -sr1_rh_supramarginal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness -" - -sr2_rh_supramarginal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness -" - -sr1_rh_supramarginal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_supramarginal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_supramarginal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness -" - -hm2_rh_supramarginal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness -" - -hm1_rh_supramarginal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_supramarginal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_supramarginal_fac =~ rh_supramarginal_thickness - -#age factor -agefac =~ age -" - -####### rh_frontalpole_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_frontalpole_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_frontalpole_fac =~ rh_frontalpole_thickness -" - -fm2v3_rh_frontalpole_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_frontalpole_fac =~ rh_frontalpole_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_frontalpole_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness -" - -fm1v3_rh_frontalpole_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_frontalpole_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness -" - -sr2_rh_frontalpole_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness -" - -sr1_rh_frontalpole_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness - -#age factor -agefac =~ age -" - -sr2_rh_frontalpole_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_frontalpole_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness -" - -hm2_rh_frontalpole_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness -" - -hm1_rh_frontalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness - -#age factor -agefac =~ age -" - -hm2_rh_frontalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_frontalpole_fac =~ rh_frontalpole_thickness - -#age factor -agefac =~ age -" - -####### rh_temporalpole_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_temporalpole_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_temporalpole_fac =~ rh_temporalpole_thickness -" - -fm2v3_rh_temporalpole_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_temporalpole_fac =~ rh_temporalpole_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_temporalpole_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness -" - -fm1v3_rh_temporalpole_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness - -#age factor -agefac =~ age -" -# Do the same for self-report models only -sr1_rh_temporalpole_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness -" - -sr2_rh_temporalpole_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness -" - -sr1_rh_temporalpole_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness - -#age factor -agefac =~ age -" - -sr2_rh_temporalpole_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_temporalpole_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness -" - -hm2_rh_temporalpole_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness -" - -hm1_rh_temporalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness - -#age factor -agefac =~ age -" - -hm2_rh_temporalpole_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_temporalpole_fac =~ rh_temporalpole_thickness - -#age factor -agefac =~ age -" - -####### rh_transversetemporal_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_transversetemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_transversetemporal_fac =~ rh_transversetemporal_thickness -" - -fm2v3_rh_transversetemporal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_transversetemporal_fac =~ rh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_transversetemporal_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness -" - -fm1v3_rh_transversetemporal_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_transversetemporal_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness -" - -sr2_rh_transversetemporal_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness -" - -sr1_rh_transversetemporal_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -sr2_rh_transversetemporal_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness - -#age factor -agefac =~ age -" -# And for hormone models only -hm1_rh_transversetemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness -" - -hm2_rh_transversetemporal_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness -" - -hm1_rh_transversetemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -hm2_rh_transversetemporal_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_transversetemporal_fac =~ rh_transversetemporal_thickness - -#age factor -agefac =~ age -" - -####### rh_insula_thickness ####### - -# Now build the first one, ADR and GON correlate with thickness -# (note that lavaan automatically shows correlations for ADR and GON and thickness) -fm2v3_rh_insula_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_insula_fac =~ rh_insula_thickness -" - -fm2v3_rh_insula_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -adrenal_sr =~ PDS2 + PDS3 + PBIP2 -gonadal_sr =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -adrenal =~ sal_dhea + sal_test + adrenal_sr -gonadal =~ sal_estr + gonadal_sr - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#covary observed l_infpar and latent neuroendo systems by tricking lavaan -# (remember that lavaan always fixes the first loading to 1) -rh_insula_fac =~ rh_insula_thickness - -#age factor -agefac =~ age -" - -# Check the thickness correlation with the one factor PUB latent variable, too -fm1v3_rh_insula_cor <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_insula_fac =~ rh_insula_thickness -" - -fm1v3_rh_insula_corage <- " -#Latent Variables - -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Self-Report -pub_sr =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#BioVars -pub_bio =~ sal_dhea + sal_estr + sal_test - -#Neuroendocrine Systems (Saliva + Hair + Qs) - Level 3 -puberty =~ pub_sr + pub_bio - -#Covariances for Saliva Sample Day -dhea1 ~~ estr1 + test1 -estr1 ~~ test1 -dhea2 ~~ estr2 + test2 -estr2 ~~ test2 -dhea3 ~~ estr3 + test3 -estr3 ~~ test3 -dhea4 ~~ estr4 + test4 -estr4 ~~ test4 - -#thickness factor -rh_insula_fac =~ rh_insula_thickness - -#age factor -agefac =~ age -" - -# Do the same for self-report models only -sr1_rh_insula_cor <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_insula_fac =~ rh_insula_thickness -" - -sr2_rh_insula_cor <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_insula_fac =~ rh_insula_thickness -" - -sr1_rh_insula_corage <- " -#Latent Neuroendocrine Systems -puberty =~ PDS1 + PDS2 + PDS3 + PDS4 + PDS6 + PBIP1 + PBIP2 - -#thickness factor -rh_insula_fac =~ rh_insula_thickness - -#age factor -agefac =~ age -" - -sr2_rh_insula_corage <- " -#Latent Neuroendocrine Systems -adrenal =~ PDS2 + PDS3 + PBIP2 -gonadal =~ PDS1 + PDS4 + PDS6 + PBIP1 - -#thickness factor -rh_insula_fac =~ rh_insula_thickness - -#age factor -agefac =~ age -" - -# And for hormone models only -hm1_rh_insula_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_insula_fac =~ rh_insula_thickness -" - -hm2_rh_insula_cor <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_insula_fac =~ rh_insula_thickness -" - -hm1_rh_insula_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -puberty =~ sal_dhea + sal_estr + sal_test - -#thickness factor -rh_insula_fac =~ rh_insula_thickness - -#age factor -agefac =~ age -" - -hm2_rh_insula_corage <- " -#Saliva - Level 1 -sal_dhea =~ dhea1 + dhea2 + dhea3 + dhea4 -sal_estr =~ estr1 + estr2 + estr3 + estr4 -sal_test =~ test1 + test2 + test3 + test4 - -#Latent Neuroendocrine Systems -adrenal =~ sal_dhea + sal_test - -#thickness factor -rh_insula_fac =~ rh_insula_thickness - -#age factor -agefac =~ age -" - -##### FIT AND SUMMARY ALL MODELS ###### - -# Fit models lh_bankssts -fit_fm2v3_lh_bankssts_cor <- cfa(fm2v3_lh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_bankssts_cor <- cfa(fm1v3_lh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_bankssts_cor <- cfa(sr1_lh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_bankssts_cor <- cfa(sr2_lh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_bankssts_cor <- cfa(hm1_lh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_bankssts_cor <- cfa(hm2_lh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_bankssts_corage <- cfa(fm2v3_lh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_bankssts_corage <- cfa(fm1v3_lh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_bankssts_corage <- cfa(sr1_lh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_bankssts_corage <- cfa(sr2_lh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_bankssts_corage <- cfa(hm1_lh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_bankssts_corage <- cfa(hm2_lh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models lh_bankssts -summary(fit_fm2v3_lh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_bankssts_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_bankssts_corage, fit.measures = T, standardized = T) - - - -# Fit models - lh_caudalanteriorcingulate - -#brainvars <- c("lh_bankssts", "lh_caudalanteriorcingulate") - -#for (i in brainvars) { -# currentmodel = paste("fm2v3_",i,"_cor",sep="") - -#paste("fit_fm2v3_",i,"_cor",sep="") <- cfa(model = "currentmodel", data = data, estimator = "ML", -# missing = "ML", verbose = T) -#} - - -fit_fm2v3_lh_caudalanteriorcingulate_cor <- cfa(fm2v3_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_caudalanteriorcingulate_cor <- cfa(fm1v3_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_caudalanteriorcingulate_cor <- cfa(sr1_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_caudalanteriorcingulate_cor <- cfa(sr2_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_caudalanteriorcingulate_cor <- cfa(hm1_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_caudalanteriorcingulate_cor <- cfa(hm2_lh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_caudalanteriorcingulate_corage <- cfa(fm2v3_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_caudalanteriorcingulate_corage <- cfa(fm1v3_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_caudalanteriorcingulate_corage <- cfa(sr1_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_caudalanteriorcingulate_corage <- cfa(sr2_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_caudalanteriorcingulate_corage <- cfa(hm1_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_caudalanteriorcingulate_corage <- cfa(hm2_lh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_caudalanteriorcingulate -summary(fit_fm2v3_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) - - -# Fit models - lh_caudalmiddlefrontal -fit_fm2v3_lh_caudalmiddlefrontal_cor <- cfa(fm2v3_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_caudalmiddlefrontal_cor <- cfa(fm1v3_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_caudalmiddlefrontal_cor <- cfa(sr1_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_caudalmiddlefrontal_cor <- cfa(sr2_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_caudalmiddlefrontal_cor <- cfa(hm1_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_caudalmiddlefrontal_cor <- cfa(hm2_lh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_caudalmiddlefrontal_corage <- cfa(fm2v3_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_caudalmiddlefrontal_corage <- cfa(fm1v3_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_caudalmiddlefrontal_corage <- cfa(sr1_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_caudalmiddlefrontal_corage <- cfa(sr2_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_caudalmiddlefrontal_corage <- cfa(hm1_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_caudalmiddlefrontal_corage <- cfa(hm2_lh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_caudalmiddlefrontal -summary(fit_fm2v3_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_cuneus -fit_fm2v3_lh_cuneus_cor <- cfa(fm2v3_lh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_cuneus_cor <- cfa(fm1v3_lh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_cuneus_cor <- cfa(sr1_lh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_cuneus_cor <- cfa(sr2_lh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_cuneus_cor <- cfa(hm1_lh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_cuneus_cor <- cfa(hm2_lh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_cuneus_corage <- cfa(fm2v3_lh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_cuneus_corage <- cfa(fm1v3_lh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_cuneus_corage <- cfa(sr1_lh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_cuneus_corage <- cfa(sr2_lh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_cuneus_corage <- cfa(hm1_lh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_cuneus_corage <- cfa(hm2_lh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - - -# Summary Stats for models - lh_cuneus -summary(fit_fm2v3_lh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_cuneus_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_cuneus_corage, fit.measures = T, standardized = T) - -# Fit models - lh_entorhinal -fit_fm2v3_lh_entorhinal_cor <- cfa(fm2v3_lh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_entorhinal_cor <- cfa(fm1v3_lh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_entorhinal_cor <- cfa(sr1_lh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_entorhinal_cor <- cfa(sr2_lh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_entorhinal_cor <- cfa(hm1_lh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_entorhinal_cor <- cfa(hm2_lh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_entorhinal_corage <- cfa(fm2v3_lh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_entorhinal_corage <- cfa(fm1v3_lh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_entorhinal_corage <- cfa(sr1_lh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_entorhinal_corage <- cfa(sr2_lh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_entorhinal_corage <- cfa(hm1_lh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_entorhinal_corage <- cfa(hm2_lh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models- lh_entorhinal -summary(fit_fm2v3_lh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_entorhinal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_entorhinal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_fusiform -fit_fm2v3_lh_fusiform_cor <- cfa(fm2v3_lh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_fusiform_cor <- cfa(fm1v3_lh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_fusiform_cor <- cfa(sr1_lh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_fusiform_cor <- cfa(sr2_lh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_fusiform_cor <- cfa(hm1_lh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_fusiform_cor <- cfa(hm2_lh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T,) - -fit_fm2v3_lh_fusiform_corage <- cfa(fm2v3_lh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_fusiform_corage <- cfa(fm1v3_lh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_fusiform_corage <- cfa(sr1_lh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_fusiform_corage <- cfa(sr2_lh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_fusiform_corage <- cfa(hm1_lh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_fusiform_corage <- cfa(hm2_lh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T,) - - -# Summary Stats for models - lh_fusiform -summary(fit_fm2v3_lh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_fusiform_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_fusiform_corage, fit.measures = T, standardized = T) - -# Fit models - lh_inferiorparietal -fit_fm2v3_lh_inferiorparietal_cor <- cfa(fm2v3_lh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_inferiorparietal_cor <- cfa(fm1v3_lh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_inferiorparietal_cor <- cfa(sr1_lh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_inferiorparietal_cor <- cfa(sr2_lh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_inferiorparietal_cor <- cfa(hm1_lh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_inferiorparietal_cor <- cfa(hm2_lh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_inferiorparietal_corage <- cfa(fm2v3_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_inferiorparietal_corage <- cfa(fm1v3_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_inferiorparietal_corage <- cfa(sr1_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_inferiorparietal_corage <- cfa(sr2_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_inferiorparietal_corage <- cfa(hm1_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_inferiorparietal_corage <- cfa(hm2_lh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_inferiorparietal -summary(fit_fm2v3_lh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_inferiorparietal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_inferiorparietal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_inferiortemporal -fit_fm2v3_lh_inferiortemporal_cor <- cfa(fm2v3_lh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_inferiortemporal_cor <- cfa(fm1v3_lh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_inferiortemporal_cor <- cfa(sr1_lh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_inferiortemporal_cor <- cfa(sr2_lh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_inferiortemporal_cor <- cfa(hm1_lh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_inferiortemporal_cor <- cfa(hm2_lh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_inferiortemporal_corage <- cfa(fm2v3_lh_inferiortemporal_corage, data =data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_inferiortemporal_corage <- cfa(fm1v3_lh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_inferiortemporal_corage <- cfa(sr1_lh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_inferiortemporal_corage <- cfa(sr2_lh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_inferiortemporal_corage <- cfa(hm1_lh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_inferiortemporal_corage <- cfa(hm2_lh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_inferiortemporal -summary(fit_fm2v3_lh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_inferiortemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_inferiortemporal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_isthmuscingulate -fit_fm2v3_lh_isthmuscingulate_cor <- cfa(fm2v3_lh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_isthmuscingulate_cor <- cfa(fm1v3_lh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_isthmuscingulate_cor <- cfa(sr1_lh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_isthmuscingulate_cor <- cfa(sr2_lh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_isthmuscingulate_cor <- cfa(hm1_lh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_isthmuscingulate_cor <- cfa(hm2_lh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_isthmuscingulate_corage <- cfa(fm2v3_lh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_isthmuscingulate_corage <- cfa(fm1v3_lh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_isthmuscingulate_corage <- cfa(sr1_lh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_isthmuscingulate_corage <- cfa(sr2_lh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_isthmuscingulate_corage <- cfa(hm1_lh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_isthmuscingulate_corage <- cfa(hm2_lh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_isthmuscingulate -summary(fit_fm2v3_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_isthmuscingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_isthmuscingulate_corage, fit.measures = T, standardized = T) - -# Fit models - lh_lateraloccipital -fit_fm2v3_lh_lateraloccipital_cor <- cfa(fm2v3_lh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_lateraloccipital_cor <- cfa(fm1v3_lh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_lateraloccipital_cor <- cfa(sr1_lh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_lateraloccipital_cor <- cfa(sr2_lh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_lateraloccipital_cor <- cfa(hm1_lh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_lateraloccipital_cor <- cfa(hm2_lh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_lateraloccipital_corage <- cfa(fm2v3_lh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_lateraloccipital_corage <- cfa(fm1v3_lh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_lateraloccipital_corage <- cfa(sr1_lh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_lateraloccipital_corage <- cfa(sr2_lh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_lateraloccipital_corage <- cfa(hm1_lh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_lateraloccipital_corage <- cfa(hm2_lh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_lateraloccipital -summary(fit_fm2v3_lh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_lateraloccipital_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_lateraloccipital_corage, fit.measures = T, standardized = T) - -# Fit models - lh_lateralorbitofrontal -fit_fm2v3_lh_lateralorbitofrontal_cor <- cfa(fm2v3_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_lateralorbitofrontal_cor <- cfa(fm1v3_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_lateralorbitofrontal_cor <- cfa(sr1_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_lateralorbitofrontal_cor <- cfa(sr2_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_lateralorbitofrontal_cor <- cfa(hm1_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_lateralorbitofrontal_cor <- cfa(hm2_lh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_lateralorbitofrontal_corage <- cfa(fm2v3_lh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_lateralorbitofrontal_corage <- cfa(fm1v3_lh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_lateralorbitofrontal_corage <- cfa(sr1_lh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_lateralorbitofrontal_corage <- cfa(sr2_lh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_lateralorbitofrontal_corage <- cfa(hm1_lh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_lateralorbitofrontal_corage <- cfa(hm2_lh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_lateralorbitofrontal -summary(fit_fm2v3_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) - - -# Fit models - lh_lingual -fit_fm2v3_lh_lingual_cor <- cfa(fm2v3_lh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_lingual_cor <- cfa(fm1v3_lh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_lingual_cor <- cfa(sr1_lh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_lingual_cor <- cfa(sr2_lh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_lingual_cor <- cfa(hm1_lh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_lingual_cor <- cfa(hm2_lh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_lingual_corage <- cfa(fm2v3_lh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_lingual_corage <- cfa(fm1v3_lh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_lingual_corage <- cfa(sr1_lh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_lingual_corage <- cfa(sr2_lh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_lingual_corage <- cfa(hm1_lh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_lingual_corage <- cfa(hm2_lh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_lingual -summary(fit_fm2v3_lh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_lingual_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_lingual_corage, fit.measures = T, standardized = T) - -# Fit models - lh_medialorbitofrontal -fit_fm2v3_lh_medialorbitofrontal_cor <- cfa(fm2v3_lh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_medialorbitofrontal_cor <- cfa(fm1v3_lh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_medialorbitofrontal_cor <- cfa(sr1_lh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_medialorbitofrontal_cor <- cfa(sr2_lh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_medialorbitofrontal_cor <- cfa(hm1_lh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_medialorbitofrontal_cor <- cfa(hm2_lh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_medialorbitofrontal_corage <- cfa(fm2v3_lh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_medialorbitofrontal_corage <- cfa(fm1v3_lh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_medialorbitofrontal_corage <- cfa(sr1_lh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_medialorbitofrontal_corage <- cfa(sr2_lh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_medialorbitofrontal_corage <- cfa(hm1_lh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_medialorbitofrontal_corage <- cfa(hm2_lh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_medialorbitofrontal -summary(fit_fm2v3_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_medialorbitofrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_medialorbitofrontal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_middletemporal -fit_fm2v3_lh_middletemporal_cor <- cfa(fm2v3_lh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_middletemporal_cor <- cfa(fm1v3_lh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_middletemporal_cor <- cfa(sr1_lh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_middletemporal_cor <- cfa(sr2_lh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_middletemporal_cor <- cfa(hm1_lh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_middletemporal_cor <- cfa(hm2_lh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_middletemporal_corage <- cfa(fm2v3_lh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_middletemporal_corage <- cfa(fm1v3_lh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_middletemporal_corage <- cfa(sr1_lh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_middletemporal_corage <- cfa(sr2_lh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_middletemporal_corage <- cfa(hm1_lh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_middletemporal_corage <- cfa(hm2_lh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_middletemporal -summary(fit_fm2v3_lh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_middletemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_middletemporal_corage, fit.measures = T, standardized = T) - - -# Fit models - lh_parahippocampal -fit_fm2v3_lh_parahippocampal_cor <- cfa(fm2v3_lh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parahippocampal_cor <- cfa(fm1v3_lh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parahippocampal_cor <- cfa(sr1_lh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parahippocampal_cor <- cfa(sr2_lh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parahippocampal_cor <- cfa(hm1_lh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parahippocampal_cor <- cfa(hm2_lh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_parahippocampal_corage <- cfa(fm2v3_lh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parahippocampal_corage <- cfa(fm1v3_lh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parahippocampal_corage <- cfa(sr1_lh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parahippocampal_corage <- cfa(sr2_lh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parahippocampal_corage <- cfa(hm1_lh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parahippocampal_corage <- cfa(hm2_lh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_parahippocampal -summary(fit_fm2v3_lh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parahippocampal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parahippocampal_corage, fit.measures = T, standardized = T) - - -# Fit models - lh_paracentral -fit_fm2v3_lh_paracentral_cor <- cfa(fm2v3_lh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_paracentral_cor <- cfa(fm1v3_lh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_paracentral_cor <- cfa(sr1_lh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_paracentral_cor <- cfa(sr2_lh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_paracentral_cor <- cfa(hm1_lh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_paracentral_cor <- cfa(hm2_lh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_paracentral_corage <- cfa(fm2v3_lh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_paracentral_corage <- cfa(fm1v3_lh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_paracentral_corage <- cfa(sr1_lh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_paracentral_corage <- cfa(sr2_lh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_paracentral_corage <- cfa(hm1_lh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_paracentral_corage <- cfa(hm2_lh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_paracentral -summary(fit_fm2v3_lh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_paracentral_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_paracentral_corage, fit.measures = T, standardized = T) - -# Fit models - lh_parsopercularis -fit_fm2v3_lh_parsopercularis_cor <- cfa(fm2v3_lh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parsopercularis_cor <- cfa(fm1v3_lh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parsopercularis_cor <- cfa(sr1_lh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parsopercularis_cor <- cfa(sr2_lh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parsopercularis_cor <- cfa(hm1_lh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parsopercularis_cor <- cfa(hm2_lh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_parsopercularis_corage <- cfa(fm2v3_lh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parsopercularis_corage <- cfa(fm1v3_lh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parsopercularis_corage <- cfa(sr1_lh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parsopercularis_corage <- cfa(sr2_lh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parsopercularis_corage <- cfa(hm1_lh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parsopercularis_corage <- cfa(hm2_lh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_parsopercularis -summary(fit_fm2v3_lh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parsopercularis_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parsopercularis_corage, fit.measures = T, standardized = T) - -# Fit models - lh_parsorbitalis -fit_fm2v3_lh_parsorbitalis_cor <- cfa(fm2v3_lh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parsorbitalis_cor <- cfa(fm1v3_lh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parsorbitalis_cor <- cfa(sr1_lh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parsorbitalis_cor <- cfa(sr2_lh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parsorbitalis_cor <- cfa(hm1_lh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parsorbitalis_cor <- cfa(hm2_lh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_parsorbitalis_corage <- cfa(fm2v3_lh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parsorbitalis_corage <- cfa(fm1v3_lh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parsorbitalis_corage <- cfa(sr1_lh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parsorbitalis_corage <- cfa(sr2_lh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parsorbitalis_corage <- cfa(hm1_lh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parsorbitalis_corage <- cfa(hm2_lh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_parsorbitalis -summary(fit_fm2v3_lh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parsorbitalis_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parsorbitalis_corage, fit.measures = T, standardized = T) - -# Fit models - lh_parstriangularis -fit_fm2v3_lh_parstriangularis_cor <- cfa(fm2v3_lh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parstriangularis_cor <- cfa(fm1v3_lh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parstriangularis_cor <- cfa(sr1_lh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parstriangularis_cor <- cfa(sr2_lh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parstriangularis_cor <- cfa(hm1_lh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parstriangularis_cor <- cfa(hm2_lh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_parstriangularis_corage <- cfa(fm2v3_lh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_parstriangularis_corage <- cfa(fm1v3_lh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_parstriangularis_corage <- cfa(sr1_lh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_parstriangularis_corage <- cfa(sr2_lh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_parstriangularis_corage <- cfa(hm1_lh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_parstriangularis_corage <- cfa(hm2_lh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_parstriangularis -summary(fit_fm2v3_lh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parstriangularis_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_parstriangularis_corage, fit.measures = T, standardized = T) - -# Fit models - lh_pericalcarine -fit_fm2v3_lh_pericalcarine_cor <- cfa(fm2v3_lh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_pericalcarine_cor <- cfa(fm1v3_lh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_pericalcarine_cor <- cfa(sr1_lh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_pericalcarine_cor <- cfa(sr2_lh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_pericalcarine_cor <- cfa(hm1_lh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_pericalcarine_cor <- cfa(hm2_lh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_pericalcarine_corage <- cfa(fm2v3_lh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_pericalcarine_corage <- cfa(fm1v3_lh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_pericalcarine_corage <- cfa(sr1_lh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_pericalcarine_corage <- cfa(sr2_lh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_pericalcarine_corage <- cfa(hm1_lh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_pericalcarine_corage <- cfa(hm2_lh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_pericalcarine -summary(fit_fm2v3_lh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_pericalcarine_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_pericalcarine_corage, fit.measures = T, standardized = T) - -# Fit models - lh_postcentral -fit_fm2v3_lh_postcentral_cor <- cfa(fm2v3_lh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_postcentral_cor <- cfa(fm1v3_lh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_postcentral_cor <- cfa(sr1_lh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_postcentral_cor <- cfa(sr2_lh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_postcentral_cor <- cfa(hm1_lh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_postcentral_cor <- cfa(hm2_lh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_postcentral_corage <- cfa(fm2v3_lh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_postcentral_corage <- cfa(fm1v3_lh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_postcentral_corage <- cfa(sr1_lh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_postcentral_corage <- cfa(sr2_lh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_postcentral_corage <- cfa(hm1_lh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_postcentral_corage <- cfa(hm2_lh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models -summary(fit_fm2v3_lh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_postcentral_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_postcentral_corage, fit.measures = T, standardized = T) - -# Fit models - lh_posteriorcingulate -fit_fm2v3_lh_posteriorcingulate_cor <- cfa(fm2v3_lh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_posteriorcingulate_cor <- cfa(fm1v3_lh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_posteriorcingulate_cor <- cfa(sr1_lh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_posteriorcingulate_cor <- cfa(sr2_lh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_posteriorcingulate_cor <- cfa(hm1_lh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_posteriorcingulate_cor <- cfa(hm2_lh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_posteriorcingulate_corage <- cfa(fm2v3_lh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_posteriorcingulate_corage <- cfa(fm1v3_lh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_posteriorcingulate_corage <- cfa(sr1_lh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_posteriorcingulate_corage <- cfa(sr2_lh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_posteriorcingulate_corage <- cfa(hm1_lh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_posteriorcingulate_corage <- cfa(hm2_lh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_posteriorcingulate -summary(fit_fm2v3_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_posteriorcingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_posteriorcingulate_corage, fit.measures = T, standardized = T) - -# Fit models - lh_precentral -fit_fm2v3_lh_precentral_cor <- cfa(fm2v3_lh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_precentral_cor <- cfa(fm1v3_lh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_precentral_cor <- cfa(sr1_lh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_precentral_cor <- cfa(sr2_lh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_precentral_cor <- cfa(hm1_lh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_precentral_cor <- cfa(hm2_lh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_precentral_corage <- cfa(fm2v3_lh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_precentral_corage <- cfa(fm1v3_lh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_precentral_corage <- cfa(sr1_lh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_precentral_corage <- cfa(sr2_lh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_precentral_corage <- cfa(hm1_lh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_precentral_corage <- cfa(hm2_lh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_precentral -summary(fit_fm2v3_lh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_precentral_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_precentral_corage, fit.measures = T, standardized = T) - -# Fit models - lh_precuneus -fit_fm2v3_lh_precuneus_cor <- cfa(fm2v3_lh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_precuneus_cor <- cfa(fm1v3_lh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_precuneus_cor <- cfa(sr1_lh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_precuneus_cor <- cfa(sr2_lh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_precuneus_cor <- cfa(hm1_lh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_precuneus_cor <- cfa(hm2_lh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_precuneus_corage <- cfa(fm2v3_lh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_precuneus_corage <- cfa(fm1v3_lh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_precuneus_corage <- cfa(sr1_lh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_precuneus_corage <- cfa(sr2_lh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_precuneus_corage <- cfa(hm1_lh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_precuneus_corage <- cfa(hm2_lh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_precuneus -summary(fit_fm2v3_lh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_precuneus_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_precuneus_corage, fit.measures = T, standardized = T) - -# Fit models - lh_rostralanteriorcingulate -fit_fm2v3_lh_rostralanteriorcingulate_cor <- cfa(fm2v3_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_rostralanteriorcingulate_cor <- cfa(fm1v3_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_rostralanteriorcingulate_cor <- cfa(sr1_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_rostralanteriorcingulate_cor <- cfa(sr2_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_rostralanteriorcingulate_cor <- cfa(hm1_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_rostralanteriorcingulate_cor <- cfa(hm2_lh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_rostralanteriorcingulate_corage <- cfa(fm2v3_lh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_rostralanteriorcingulate_corage <- cfa(fm1v3_lh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_rostralanteriorcingulate_corage <- cfa(sr1_lh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_rostralanteriorcingulate_corage <- cfa(sr2_lh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_rostralanteriorcingulate_corage <- cfa(hm1_lh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_rostralanteriorcingulate_corage <- cfa(hm2_lh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_rostralanteriorcingulate -summary(fit_fm2v3_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) - -# Fit models - lh_rostralmiddlefrontal -fit_fm2v3_lh_rostralmiddlefrontal_cor <- cfa(fm2v3_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_rostralmiddlefrontal_cor <- cfa(fm1v3_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_rostralmiddlefrontal_cor <- cfa(sr1_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_rostralmiddlefrontal_cor <- cfa(sr2_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_rostralmiddlefrontal_cor <- cfa(hm1_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_rostralmiddlefrontal_cor <- cfa(hm2_lh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_rostralmiddlefrontal_corage <- cfa(fm2v3_lh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_rostralmiddlefrontal_corage <- cfa(fm1v3_lh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_rostralmiddlefrontal_corage <- cfa(sr1_lh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_rostralmiddlefrontal_corage <- cfa(sr2_lh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_rostralmiddlefrontal_corage <- cfa(hm1_lh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_rostralmiddlefrontal_corage <- cfa(hm2_lh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models -summary(fit_fm2v3_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) - -# Fit models- lh_superiorfrontal -fit_fm2v3_lh_superiorfrontal_cor <- cfa(fm2v3_lh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_superiorfrontal_cor <- cfa(fm1v3_lh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_superiorfrontal_cor <- cfa(sr1_lh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_superiorfrontal_cor <- cfa(sr2_lh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_superiorfrontal_cor <- cfa(hm1_lh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_superiorfrontal_cor <- cfa(hm2_lh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_superiorfrontal_corage <- cfa(fm2v3_lh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_superiorfrontal_corage <- cfa(fm1v3_lh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_superiorfrontal_corage <- cfa(sr1_lh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_superiorfrontal_corage <- cfa(sr2_lh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_superiorfrontal_corage <- cfa(hm1_lh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_superiorfrontal_corage <- cfa(hm2_lh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_superiorfrontal -summary(fit_fm2v3_lh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_superiorfrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_superiorfrontal_corage, fit.measures = T, standardized = T) - -# Fit models- lh_superiorparietal -fit_fm2v3_lh_superiorparietal_cor <- cfa(fm2v3_lh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_superiorparietal_cor <- cfa(fm1v3_lh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_superiorparietal_cor <- cfa(sr1_lh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_superiorparietal_cor <- cfa(sr2_lh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_superiorparietal_cor <- cfa(hm1_lh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_superiorparietal_cor <- cfa(hm2_lh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_superiorparietal_corage <- cfa(fm2v3_lh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_superiorparietal_corage <- cfa(fm1v3_lh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_superiorparietal_corage <- cfa(sr1_lh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_superiorparietal_corage <- cfa(sr2_lh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_superiorparietal_corage <- cfa(hm1_lh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_superiorparietal_corage <- cfa(hm2_lh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models- lh_superiorparietal -summary(fit_fm2v3_lh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_superiorparietal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_superiorparietal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_superiortemporal -fit_fm2v3_lh_superiortemporal_cor <- cfa(fm2v3_lh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_superiortemporal_cor <- cfa(fm1v3_lh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_superiortemporal_cor <- cfa(sr1_lh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_superiortemporal_cor <- cfa(sr2_lh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_superiortemporal_cor <- cfa(hm1_lh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_superiortemporal_cor <- cfa(hm2_lh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_superiortemporal_corage <- cfa(fm2v3_lh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_superiortemporal_corage <- cfa(fm1v3_lh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_superiortemporal_corage <- cfa(sr1_lh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_superiortemporal_corage <- cfa(sr2_lh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_superiortemporal_corage <- cfa(hm1_lh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_superiortemporal_corage <- cfa(hm2_lh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_superiortemporal -summary(fit_fm2v3_lh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_superiortemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_superiortemporal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_supramarginal -fit_fm2v3_lh_supramarginal_cor <- cfa(fm2v3_lh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_supramarginal_cor <- cfa(fm1v3_lh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_supramarginal_cor <- cfa(sr1_lh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_supramarginal_cor <- cfa(sr2_lh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_supramarginal_cor <- cfa(hm1_lh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_supramarginal_cor <- cfa(hm2_lh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_supramarginal_corage <- cfa(fm2v3_lh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_supramarginal_corage <- cfa(fm1v3_lh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_supramarginal_corage <- cfa(sr1_lh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_supramarginal_corage <- cfa(sr2_lh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_supramarginal_corage <- cfa(hm1_lh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_supramarginal_corage <- cfa(hm2_lh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models-lh_supramarginal -summary(fit_fm2v3_lh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_supramarginal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_supramarginal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_frontalpole -fit_fm2v3_lh_frontalpole_cor <- cfa(fm2v3_lh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_frontalpole_cor <- cfa(fm1v3_lh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_frontalpole_cor <- cfa(sr1_lh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_frontalpole_cor <- cfa(sr2_lh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_frontalpole_cor <- cfa(hm1_lh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_frontalpole_cor <- cfa(hm2_lh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_frontalpole_corage <- cfa(fm2v3_lh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_frontalpole_corage <- cfa(fm1v3_lh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_frontalpole_corage <- cfa(sr1_lh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_frontalpole_corage <- cfa(sr2_lh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_frontalpole_corage <- cfa(hm1_lh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_frontalpole_corage <- cfa(hm2_lh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models- lh_frontalpole -summary(fit_fm2v3_lh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_frontalpole_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_frontalpole_corage, fit.measures = T, standardized = T) - - -# Fit models - lh_temporalpole -fit_fm2v3_lh_temporalpole_cor <- cfa(fm2v3_lh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_temporalpole_cor <- cfa(fm1v3_lh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_temporalpole_cor <- cfa(sr1_lh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_temporalpole_cor <- cfa(sr2_lh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_temporalpole_cor <- cfa(hm1_lh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_temporalpole_cor <- cfa(hm2_lh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_temporalpole_corage <- cfa(fm2v3_lh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_temporalpole_corage <- cfa(fm1v3_lh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_temporalpole_corage <- cfa(sr1_lh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_temporalpole_corage <- cfa(sr2_lh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_temporalpole_corage <- cfa(hm1_lh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_temporalpole_corage <- cfa(hm2_lh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_temporalpole -summary(fit_fm2v3_lh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_temporalpole_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_temporalpole_corage, fit.measures = T, standardized = T) - -# Fit models - lh_transversetemporal -fit_fm2v3_lh_transversetemporal_cor <- cfa(fm2v3_lh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_transversetemporal_cor <- cfa(fm1v3_lh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_transversetemporal_cor <- cfa(sr1_lh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_transversetemporal_cor <- cfa(sr2_lh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_transversetemporal_cor <- cfa(hm1_lh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_transversetemporal_cor <- cfa(hm2_lh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_transversetemporal_corage <- cfa(fm2v3_lh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_transversetemporal_corage <- cfa(fm1v3_lh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_transversetemporal_corage <- cfa(sr1_lh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_transversetemporal_corage <- cfa(sr2_lh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_transversetemporal_corage <- cfa(hm1_lh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_transversetemporal_corage <- cfa(hm2_lh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_transversetemporal -summary(fit_fm2v3_lh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_transversetemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_transversetemporal_corage, fit.measures = T, standardized = T) - -# Fit models - lh_insula -fit_fm2v3_lh_insula_cor <- cfa(fm2v3_lh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_insula_cor <- cfa(fm1v3_lh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_insula_cor <- cfa(sr1_lh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_insula_cor <- cfa(sr2_lh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_insula_cor <- cfa(hm1_lh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_insula_cor <- cfa(hm2_lh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_lh_insula_corage <- cfa(fm2v3_lh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_lh_insula_corage <- cfa(fm1v3_lh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_lh_insula_corage <- cfa(sr1_lh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_lh_insula_corage <- cfa(sr2_lh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_lh_insula_corage <- cfa(hm1_lh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_lh_insula_corage <- cfa(hm2_lh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - lh_insula -summary(fit_fm2v3_lh_insula_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_insula_cor, fit.measures = T, standardized = T) -summary(fit_sr1_lh_insula_cor, fit.measures = T, standardized = T) -summary(fit_sr2_lh_insula_cor, fit.measures = T, standardized = T) -summary(fit_hm1_lh_insula_cor, fit.measures = T, standardized = T) -summary(fit_hm2_lh_insula_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_lh_insula_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_lh_insula_corage, fit.measures = T, standardized = T) -summary(fit_sr1_lh_insula_corage, fit.measures = T, standardized = T) -summary(fit_sr2_lh_insula_corage, fit.measures = T, standardized = T) -summary(fit_hm1_lh_insula_corage, fit.measures = T, standardized = T) -summary(fit_hm2_lh_insula_corage, fit.measures = T, standardized = T) - -# Fit models-rh_bankssts -fit_fm2v3_rh_bankssts_cor <- cfa(fm2v3_rh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_bankssts_cor <- cfa(fm1v3_rh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_bankssts_cor <- cfa(sr1_rh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_bankssts_cor <- cfa(sr2_rh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_bankssts_cor <- cfa(hm1_rh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_bankssts_cor <- cfa(hm2_rh_bankssts_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_bankssts_corage <- cfa(fm2v3_rh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_bankssts_corage <- cfa(fm1v3_rh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_bankssts_corage <- cfa(sr1_rh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_bankssts_corage <- cfa(sr2_rh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_bankssts_corage <- cfa(hm1_rh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_bankssts_corage <- cfa(hm2_rh_bankssts_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models- rh_bankssts -summary(fit_fm2v3_rh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_bankssts_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_bankssts_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_bankssts_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_bankssts_corage, fit.measures = T, standardized = T) - - -# Fit models - rh_caudalanteriorcingulate -fit_fm2v3_rh_caudalanteriorcingulate_cor <- cfa(fm2v3_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_caudalanteriorcingulate_cor <- cfa(fm1v3_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_caudalanteriorcingulate_cor <- cfa(sr1_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_caudalanteriorcingulate_cor <- cfa(sr2_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_caudalanteriorcingulate_cor <- cfa(hm1_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_caudalanteriorcingulate_cor <- cfa(hm2_rh_caudalanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_caudalanteriorcingulate_corage <- cfa(fm2v3_rh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_caudalanteriorcingulate_corage <- cfa(fm1v3_rh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_caudalanteriorcingulate_corage <- cfa(sr1_rh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_caudalanteriorcingulate_corage <- cfa(sr2_rh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_caudalanteriorcingulate_corage <- cfa(hm1_rh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_caudalanteriorcingulate_corage <- cfa(hm2_rh_caudalanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_caudalanteriorcingulate -summary(fit_fm2v3_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_caudalanteriorcingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_caudalanteriorcingulate_corage, fit.measures = T, standardized = T) - -# Fit models - rh_caudalmiddlefrontal -fit_fm2v3_rh_caudalmiddlefrontal_cor <- cfa(fm2v3_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_caudalmiddlefrontal_cor <- cfa(fm1v3_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_caudalmiddlefrontal_cor <- cfa(sr1_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_caudalmiddlefrontal_cor <- cfa(sr2_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_caudalmiddlefrontal_cor <- cfa(hm1_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_caudalmiddlefrontal_cor <- cfa(hm2_rh_caudalmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_caudalmiddlefrontal_corage <- cfa(fm2v3_rh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_caudalmiddlefrontal_corage <- cfa(fm1v3_rh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_caudalmiddlefrontal_corage <- cfa(sr1_rh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_caudalmiddlefrontal_corage <- cfa(sr2_rh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_caudalmiddlefrontal_corage <- cfa(hm1_rh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_caudalmiddlefrontal_corage <- cfa(hm2_rh_caudalmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_caudalmiddlefrontal -summary(fit_fm2v3_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_caudalmiddlefrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_caudalmiddlefrontal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_cuneus -fit_fm2v3_rh_cuneus_cor <- cfa(fm2v3_rh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_cuneus_cor <- cfa(fm1v3_rh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_cuneus_cor <- cfa(sr1_rh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_cuneus_cor <- cfa(sr2_rh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_cuneus_cor <- cfa(hm1_rh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_cuneus_cor <- cfa(hm2_rh_cuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_cuneus_corage <- cfa(fm2v3_rh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_cuneus_corage <- cfa(fm1v3_rh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_cuneus_corage <- cfa(sr1_rh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_cuneus_corage <- cfa(sr2_rh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_cuneus_corage <- cfa(hm1_rh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_cuneus_corage <- cfa(hm2_rh_cuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_cuneus -summary(fit_fm2v3_rh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_cuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_cuneus_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_cuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_cuneus_corage, fit.measures = T, standardized = T) - -# Fit models - rh_entorhinal -fit_fm2v3_rh_entorhinal_cor <- cfa(fm2v3_rh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_entorhinal_cor <- cfa(fm1v3_rh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_entorhinal_cor <- cfa(sr1_rh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_entorhinal_cor <- cfa(sr2_rh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_entorhinal_cor <- cfa(hm1_rh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_entorhinal_cor <- cfa(hm2_rh_entorhinal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_entorhinal_corage <- cfa(fm2v3_rh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_entorhinal_corage <- cfa(fm1v3_rh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_entorhinal_corage <- cfa(sr1_rh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_entorhinal_corage <- cfa(sr2_rh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_entorhinal_corage <- cfa(hm1_rh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_entorhinal_corage <- cfa(hm2_rh_entorhinal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_entorhinal -summary(fit_fm2v3_rh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_entorhinal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_entorhinal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_entorhinal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_entorhinal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_fusiform -fit_fm2v3_rh_fusiform_cor <- cfa(fm2v3_rh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_fusiform_cor <- cfa(fm1v3_rh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_fusiform_cor <- cfa(sr1_rh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_fusiform_cor <- cfa(sr2_rh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_fusiform_cor <- cfa(hm1_rh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_fusiform_cor <- cfa(hm2_rh_fusiform_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_fusiform_corage <- cfa(fm2v3_rh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_fusiform_corage <- cfa(fm1v3_rh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_fusiform_corage <- cfa(sr1_rh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_fusiform_corage <- cfa(sr2_rh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_fusiform_corage <- cfa(hm1_rh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_fusiform_corage <- cfa(hm2_rh_fusiform_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_fusiform -summary(fit_fm2v3_rh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_fusiform_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_fusiform_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_fusiform_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_fusiform_corage, fit.measures = T, standardized = T) - -# Fit models - rh_inferiorparietal -fit_fm2v3_rh_inferiorparietal_cor <- cfa(fm2v3_rh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_inferiorparietal_cor <- cfa(fm1v3_rh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_inferiorparietal_cor <- cfa(sr1_rh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_inferiorparietal_cor <- cfa(sr2_rh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_inferiorparietal_cor <- cfa(hm1_rh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_inferiorparietal_cor <- cfa(hm2_rh_inferiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_inferiorparietal_corage <- cfa(fm2v3_rh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_inferiorparietal_corage <- cfa(fm1v3_rh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_inferiorparietal_corage <- cfa(sr1_rh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_inferiorparietal_corage <- cfa(sr2_rh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_inferiorparietal_corage <- cfa(hm1_rh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_inferiorparietal_corage <- cfa(hm2_rh_inferiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_inferiorparietal -summary(fit_fm2v3_rh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_inferiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_inferiorparietal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_inferiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_inferiorparietal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_inferiortemporal -fit_fm2v3_rh_inferiortemporal_cor <- cfa(fm2v3_rh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_inferiortemporal_cor <- cfa(fm1v3_rh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_inferiortemporal_cor <- cfa(sr1_rh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_inferiortemporal_cor <- cfa(sr2_rh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_inferiortemporal_cor <- cfa(hm1_rh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_inferiortemporal_cor <- cfa(hm2_rh_inferiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_inferiortemporal_corage <- cfa(fm2v3_rh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_inferiortemporal_corage <- cfa(fm1v3_rh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_inferiortemporal_corage <- cfa(sr1_rh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_inferiortemporal_corage <- cfa(sr2_rh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_inferiortemporal_corage <- cfa(hm1_rh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_inferiortemporal_corage <- cfa(hm2_rh_inferiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_inferiortemporal -summary(fit_fm2v3_rh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_inferiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_inferiortemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_inferiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_inferiortemporal_corage, fit.measures = T, standardized = T) - - -# Fit models - rh_isthmuscingulate -fit_fm2v3_rh_isthmuscingulate_cor <- cfa(fm2v3_rh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_isthmuscingulate_cor <- cfa(fm1v3_rh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_isthmuscingulate_cor <- cfa(sr1_rh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_isthmuscingulate_cor <- cfa(sr2_rh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_isthmuscingulate_cor <- cfa(hm1_rh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_isthmuscingulate_cor <- cfa(hm2_rh_isthmuscingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_isthmuscingulate_corage <- cfa(fm2v3_rh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_isthmuscingulate_corage <- cfa(fm1v3_rh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_isthmuscingulate_corage <- cfa(sr1_rh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_isthmuscingulate_corage <- cfa(sr2_rh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_isthmuscingulate_corage <- cfa(hm1_rh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_isthmuscingulate_corage <- cfa(hm2_rh_isthmuscingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models- rh_isthmuscingulate -summary(fit_fm2v3_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_isthmuscingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_isthmuscingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_isthmuscingulate_corage, fit.measures = T, standardized = T) - -# Fit models - rh_lateraloccipital -fit_fm2v3_rh_lateraloccipital_cor <- cfa(fm2v3_rh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_lateraloccipital_cor <- cfa(fm1v3_rh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_lateraloccipital_cor <- cfa(sr1_rh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_lateraloccipital_cor <- cfa(sr2_rh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_lateraloccipital_cor <- cfa(hm1_rh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_lateraloccipital_cor <- cfa(hm2_rh_lateraloccipital_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_lateraloccipital_corage <- cfa(fm2v3_rh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_lateraloccipital_corage <- cfa(fm1v3_rh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_lateraloccipital_corage <- cfa(sr1_rh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_lateraloccipital_corage <- cfa(sr2_rh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_lateraloccipital_corage <- cfa(hm1_rh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_lateraloccipital_corage <- cfa(hm2_rh_lateraloccipital_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_lateraloccipital -summary(fit_fm2v3_rh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_lateraloccipital_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_lateraloccipital_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_lateraloccipital_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_lateraloccipital_corage, fit.measures = T, standardized = T) - -# Fit models - rh_lateralorbitofrontal -fit_fm2v3_rh_lateralorbitofrontal_cor <- cfa(fm2v3_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_lateralorbitofrontal_cor <- cfa(fm1v3_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_lateralorbitofrontal_cor <- cfa(sr1_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_lateralorbitofrontal_cor <- cfa(sr2_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_lateralorbitofrontal_cor <- cfa(hm1_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_lateralorbitofrontal_cor <- cfa(hm2_rh_lateralorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_lateralorbitofrontal_corage <- cfa(fm2v3_rh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_lateralorbitofrontal_corage <- cfa(fm1v3_rh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_lateralorbitofrontal_corage <- cfa(sr1_rh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_lateralorbitofrontal_corage <- cfa(sr2_rh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_lateralorbitofrontal_corage <- cfa(hm1_rh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_lateralorbitofrontal_corage <- cfa(hm2_rh_lateralorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_lateralorbitofrontal -summary(fit_fm2v3_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_lateralorbitofrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_lateralorbitofrontal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_lingual -fit_fm2v3_rh_lingual_cor <- cfa(fm2v3_rh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_lingual_cor <- cfa(fm1v3_rh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_lingual_cor <- cfa(sr1_rh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_lingual_cor <- cfa(sr2_rh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_lingual_cor <- cfa(hm1_rh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_lingual_cor <- cfa(hm2_rh_lingual_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_lingual_corage <- cfa(fm2v3_rh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_lingual_corage <- cfa(fm1v3_rh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_lingual_corage <- cfa(sr1_rh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_lingual_corage <- cfa(sr2_rh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_lingual_corage <- cfa(hm1_rh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_lingual_corage <- cfa(hm2_rh_lingual_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_lingual -summary(fit_fm2v3_rh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_lingual_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_lingual_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_lingual_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_lingual_corage, fit.measures = T, standardized = T) - -# Fit models - rh_medialorbitofrontal -fit_fm2v3_rh_medialorbitofrontal_cor <- cfa(fm2v3_rh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_medialorbitofrontal_cor <- cfa(fm1v3_rh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_medialorbitofrontal_cor <- cfa(sr1_rh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_medialorbitofrontal_cor <- cfa(sr2_rh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_medialorbitofrontal_cor <- cfa(hm1_rh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_medialorbitofrontal_cor <- cfa(hm2_rh_medialorbitofrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_medialorbitofrontal_corage <- cfa(fm2v3_rh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_medialorbitofrontal_corage <- cfa(fm1v3_rh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_medialorbitofrontal_corage <- cfa(sr1_rh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_medialorbitofrontal_corage <- cfa(sr2_rh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_medialorbitofrontal_corage <- cfa(hm1_rh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_medialorbitofrontal_corage <- cfa(hm2_rh_medialorbitofrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_medialorbitofrontal -summary(fit_fm2v3_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_medialorbitofrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_medialorbitofrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_medialorbitofrontal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_middletemporal -fit_fm2v3_rh_middletemporal_cor <- cfa(fm2v3_rh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_middletemporal_cor <- cfa(fm1v3_rh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_middletemporal_cor <- cfa(sr1_rh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_middletemporal_cor <- cfa(sr2_rh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_middletemporal_cor <- cfa(hm1_rh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_middletemporal_cor <- cfa(hm2_rh_middletemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_middletemporal_corage <- cfa(fm2v3_rh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_middletemporal_corage <- cfa(fm1v3_rh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_middletemporal_corage <- cfa(sr1_rh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_middletemporal_corage <- cfa(sr2_rh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_middletemporal_corage <- cfa(hm1_rh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_middletemporal_corage <- cfa(hm2_rh_middletemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_middletemporal -summary(fit_fm2v3_rh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_middletemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_middletemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_middletemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_middletemporal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_parahippocampal -fit_fm2v3_rh_parahippocampal_cor <- cfa(fm2v3_rh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_parahippocampal_cor <- cfa(fm1v3_rh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parahippocampal_cor <- cfa(sr1_rh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parahippocampal_cor <- cfa(sr2_rh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parahippocampal_cor <- cfa(hm1_rh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parahippocampal_cor <- cfa(hm2_rh_parahippocampal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_parahippocampal_corage <- cfa(fm2v3_rh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_parahippocampal_corage <- cfa(fm1v3_rh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parahippocampal_corage <- cfa(sr1_rh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parahippocampal_corage <- cfa(sr2_rh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parahippocampal_corage <- cfa(hm1_rh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parahippocampal_corage <- cfa(hm2_rh_parahippocampal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_parahippocampal -summary(fit_fm2v3_rh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parahippocampal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parahippocampal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parahippocampal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parahippocampal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_paracentral -fit_fm2v3_rh_paracentral_cor <- cfa(fm2v3_rh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_paracentral_cor <- cfa(fm1v3_rh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_paracentral_cor <- cfa(sr1_rh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_paracentral_cor <- cfa(sr2_rh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_paracentral_cor <- cfa(hm1_rh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_paracentral_cor <- cfa(hm2_rh_paracentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_paracentral_corage <- cfa(fm2v3_rh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_paracentral_corage <- cfa(fm1v3_rh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_paracentral_corage <- cfa(sr1_rh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_paracentral_corage <- cfa(sr2_rh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_paracentral_corage <- cfa(hm1_rh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_paracentral_corage <- cfa(hm2_rh_paracentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_paracentral -summary(fit_fm2v3_rh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_paracentral_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_paracentral_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_paracentral_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_paracentral_corage, fit.measures = T, standardized = T) - -# Fit models- rh_parsopercularis -fit_fm2v3_rh_parsopercularis_cor <- cfa(fm2v3_rh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T ) -fit_fm1v3_rh_parsopercularis_cor <- cfa(fm1v3_rh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parsopercularis_cor <- cfa(sr1_rh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parsopercularis_cor <- cfa(sr2_rh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parsopercularis_cor <- cfa(hm1_rh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parsopercularis_cor <- cfa(hm2_rh_parsopercularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_parsopercularis_corage <- cfa(fm2v3_rh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T ) -fit_fm1v3_rh_parsopercularis_corage <- cfa(fm1v3_rh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parsopercularis_corage <- cfa(sr1_rh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parsopercularis_corage <- cfa(sr2_rh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parsopercularis_corage <- cfa(hm1_rh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parsopercularis_corage <- cfa(hm2_rh_parsopercularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_parsopercularis -summary(fit_fm2v3_rh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parsopercularis_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parsopercularis_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parsopercularis_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parsopercularis_corage, fit.measures = T, standardized = T) - -# Fit models - rh_parsorbitalis -fit_fm2v3_rh_parsorbitalis_cor <- cfa(fm2v3_rh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_parsorbitalis_cor <- cfa(fm1v3_rh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parsorbitalis_cor <- cfa(sr1_rh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parsorbitalis_cor <- cfa(sr2_rh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parsorbitalis_cor <- cfa(hm1_rh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parsorbitalis_cor <- cfa(hm2_rh_parsorbitalis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_parsorbitalis_corage <- cfa(fm2v3_rh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_parsorbitalis_corage <- cfa(fm1v3_rh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parsorbitalis_corage <- cfa(sr1_rh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parsorbitalis_corage <- cfa(sr2_rh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parsorbitalis_corage <- cfa(hm1_rh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parsorbitalis_corage <- cfa(hm2_rh_parsorbitalis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_parsorbitalis -summary(fit_fm2v3_rh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parsorbitalis_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parsorbitalis_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parsorbitalis_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parsorbitalis_corage, fit.measures = T, standardized = T) - -# Fit models - rh_parstriangularis -fit_fm2v3_rh_parstriangularis_cor <- cfa(fm2v3_rh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_parstriangularis_cor <- cfa(fm1v3_rh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parstriangularis_cor <- cfa(sr1_rh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parstriangularis_cor <- cfa(sr2_rh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parstriangularis_cor <- cfa(hm1_rh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parstriangularis_cor <- cfa(hm2_rh_parstriangularis_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_parstriangularis_corage <- cfa(fm2v3_rh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_parstriangularis_corage <- cfa(fm1v3_rh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_parstriangularis_corage <- cfa(sr1_rh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_parstriangularis_corage <- cfa(sr2_rh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_parstriangularis_corage <- cfa(hm1_rh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_parstriangularis_corage <- cfa(hm2_rh_parstriangularis_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_parstriangularis -summary(fit_fm2v3_rh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parstriangularis_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parstriangularis_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_parstriangularis_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_parstriangularis_corage, fit.measures = T, standardized = T) - -# Fit models - rh_pericalcarine -fit_fm2v3_rh_pericalcarine_cor <- cfa(fm2v3_rh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_pericalcarine_cor <- cfa(fm1v3_rh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_pericalcarine_cor <- cfa(sr1_rh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_pericalcarine_cor <- cfa(sr2_rh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_pericalcarine_cor <- cfa(hm1_rh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_pericalcarine_cor <- cfa(hm2_rh_pericalcarine_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_pericalcarine_corage <- cfa(fm2v3_rh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_pericalcarine_corage <- cfa(fm1v3_rh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_pericalcarine_corage <- cfa(sr1_rh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_pericalcarine_corage <- cfa(sr2_rh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_pericalcarine_corage <- cfa(hm1_rh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_pericalcarine_corage <- cfa(hm2_rh_pericalcarine_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_pericalcarine -summary(fit_fm2v3_rh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_pericalcarine_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_pericalcarine_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_pericalcarine_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_pericalcarine_corage, fit.measures = T, standardized = T) - -# Fit models - rh_postcentral -fit_fm2v3_rh_postcentral_cor <- cfa(fm2v3_rh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_postcentral_cor <- cfa(fm1v3_rh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_postcentral_cor <- cfa(sr1_rh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_postcentral_cor <- cfa(sr2_rh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_postcentral_cor <- cfa(hm1_rh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_postcentral_cor <- cfa(hm2_rh_postcentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_postcentral_corage <- cfa(fm2v3_rh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_postcentral_corage <- cfa(fm1v3_rh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_postcentral_corage <- cfa(sr1_rh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_postcentral_corage <- cfa(sr2_rh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_postcentral_corage <- cfa(hm1_rh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_postcentral_corage <- cfa(hm2_rh_postcentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_postcentral -summary(fit_fm2v3_rh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_postcentral_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_postcentral_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_postcentral_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_postcentral_corage, fit.measures = T, standardized = T) - -# Fit models - rh_posteriorcingulate -fit_fm2v3_rh_posteriorcingulate_cor <- cfa(fm2v3_rh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_posteriorcingulate_cor <- cfa(fm1v3_rh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_posteriorcingulate_cor <- cfa(sr1_rh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_posteriorcingulate_cor <- cfa(sr2_rh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_posteriorcingulate_cor <- cfa(hm1_rh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_posteriorcingulate_cor <- cfa(hm2_rh_posteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_posteriorcingulate_corage <- cfa(fm2v3_rh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_posteriorcingulate_corage <- cfa(fm1v3_rh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_posteriorcingulate_corage <- cfa(sr1_rh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_posteriorcingulate_corage <- cfa(sr2_rh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_posteriorcingulate_corage <- cfa(hm1_rh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_posteriorcingulate_corage <- cfa(hm2_rh_posteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_posteriorcingulate -summary(fit_fm2v3_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_posteriorcingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_posteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_posteriorcingulate_corage, fit.measures = T, standardized = T) - -# Fit models- rh_precentral -fit_fm2v3_rh_precentral_cor <- cfa(fm2v3_rh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_precentral_cor <- cfa(fm1v3_rh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_precentral_cor <- cfa(sr1_rh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_precentral_cor <- cfa(sr2_rh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_precentral_cor <- cfa(hm1_rh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_precentral_cor <- cfa(hm2_rh_precentral_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_precentral_corage <- cfa(fm2v3_rh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_precentral_corage <- cfa(fm1v3_rh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_precentral_corage <- cfa(sr1_rh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_precentral_corage <- cfa(sr2_rh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_precentral_corage <- cfa(hm1_rh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_precentral_corage <- cfa(hm2_rh_precentral_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_precentral -summary(fit_fm2v3_rh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_precentral_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_precentral_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_precentral_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_precentral_corage, fit.measures = T, standardized = T) - -# Fit models - rh_precuneus -fit_fm2v3_rh_precuneus_cor <- cfa(fm2v3_rh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_precuneus_cor <- cfa(fm1v3_rh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_precuneus_cor <- cfa(sr1_rh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_precuneus_cor <- cfa(sr2_rh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_precuneus_cor <- cfa(hm1_rh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_precuneus_cor <- cfa(hm2_rh_precuneus_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_precuneus_corage <- cfa(fm2v3_rh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_precuneus_corage <- cfa(fm1v3_rh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_precuneus_corage <- cfa(sr1_rh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_precuneus_corage <- cfa(sr2_rh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_precuneus_corage <- cfa(hm1_rh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_precuneus_corage <- cfa(hm2_rh_precuneus_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_precuneus -summary(fit_fm2v3_rh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_precuneus_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_precuneus_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_precuneus_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_precuneus_corage, fit.measures = T, standardized = T) - -# Fit models - rostralanteriorcingulate -fit_fm2v3_rh_rostralanteriorcingulate_cor <- cfa(fm2v3_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_rostralanteriorcingulate_cor <- cfa(fm1v3_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_rostralanteriorcingulate_cor <- cfa(sr1_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_rostralanteriorcingulate_cor <- cfa(sr2_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_rostralanteriorcingulate_cor <- cfa(hm1_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_rostralanteriorcingulate_cor <- cfa(hm2_rh_rostralanteriorcingulate_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_rostralanteriorcingulate_corage <- cfa(fm2v3_rh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_rostralanteriorcingulate_corage <- cfa(fm1v3_rh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_rostralanteriorcingulate_corage <- cfa(sr1_rh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_rostralanteriorcingulate_corage <- cfa(sr2_rh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_rostralanteriorcingulate_corage <- cfa(hm1_rh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_rostralanteriorcingulate_corage <- cfa(hm2_rh_rostralanteriorcingulate_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rostralanteriorcingulate -summary(fit_fm2v3_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_rostralanteriorcingulate_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_rostralanteriorcingulate_corage, fit.measures = T, standardized = T) - -# Fit models - rh_rostralmiddlefrontal -fit_fm2v3_rh_rostralmiddlefrontal_cor <- cfa(fm2v3_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_rostralmiddlefrontal_cor <- cfa(fm1v3_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_rostralmiddlefrontal_cor <- cfa(sr1_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_rostralmiddlefrontal_cor <- cfa(sr2_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_rostralmiddlefrontal_cor <- cfa(hm1_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_rostralmiddlefrontal_cor <- cfa(hm2_rh_rostralmiddlefrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_rostralmiddlefrontal_corage <- cfa(fm2v3_rh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_rostralmiddlefrontal_corage <- cfa(fm1v3_rh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_rostralmiddlefrontal_corage <- cfa(sr1_rh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_rostralmiddlefrontal_corage <- cfa(sr2_rh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_rostralmiddlefrontal_corage <- cfa(hm1_rh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_rostralmiddlefrontal_corage <- cfa(hm2_rh_rostralmiddlefrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_rostralmiddlefrontal -summary(fit_fm2v3_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_rostralmiddlefrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_rostralmiddlefrontal_corage, fit.measures = T, standardized = T) - -# Fit models - superiorfrontal -fit_fm2v3_rh_superiorfrontal_cor <- cfa(fm2v3_rh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_superiorfrontal_cor <- cfa(fm1v3_rh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_superiorfrontal_cor <- cfa(sr1_rh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_superiorfrontal_cor <- cfa(sr2_rh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_superiorfrontal_cor <- cfa(hm1_rh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_superiorfrontal_cor <- cfa(hm2_rh_superiorfrontal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_superiorfrontal_corage <- cfa(fm2v3_rh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_superiorfrontal_corage <- cfa(fm1v3_rh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_superiorfrontal_corage <- cfa(sr1_rh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_superiorfrontal_corage <- cfa(sr2_rh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_superiorfrontal_corage <- cfa(hm1_rh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_superiorfrontal_corage <- cfa(hm2_rh_superiorfrontal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - superiorfrontal -summary(fit_fm2v3_rh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_superiorfrontal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_superiorfrontal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_superiorfrontal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_superiorfrontal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_superiorparietal -fit_fm2v3_rh_superiorparietal_cor <- cfa(fm2v3_rh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_superiorparietal_cor <- cfa(fm1v3_rh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_superiorparietal_cor <- cfa(sr1_rh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_superiorparietal_cor <- cfa(sr2_rh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_superiorparietal_cor <- cfa(hm1_rh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_superiorparietal_cor <- cfa(hm2_rh_superiorparietal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_superiorparietal_corage <- cfa(fm2v3_rh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_superiorparietal_corage <- cfa(fm1v3_rh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_superiorparietal_corage <- cfa(sr1_rh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_superiorparietal_corage <- cfa(sr2_rh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_superiorparietal_corage <- cfa(hm1_rh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_superiorparietal_corage <- cfa(hm2_rh_superiorparietal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) # Summary Stats for models -summary(fit_fm2v3_rh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_superiorparietal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_superiorparietal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_superiorparietal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_superiorparietal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_superiortemporal -fit_fm2v3_rh_superiortemporal_cor <- cfa(fm2v3_rh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_superiortemporal_cor <- cfa(fm1v3_rh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_superiortemporal_cor <- cfa(sr1_rh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_superiortemporal_cor <- cfa(sr2_rh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_superiortemporal_cor <- cfa(hm1_rh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_superiortemporal_cor <- cfa(hm2_rh_superiortemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_superiortemporal_corage <- cfa(fm2v3_rh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_superiortemporal_corage <- cfa(fm1v3_rh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_superiortemporal_corage <- cfa(sr1_rh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_superiortemporal_corage <- cfa(sr2_rh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_superiortemporal_corage <- cfa(hm1_rh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_superiortemporal_corage <- cfa(hm2_rh_superiortemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_superiortemporal -summary(fit_fm2v3_rh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_superiortemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_superiortemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_superiortemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_superiortemporal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_supramarginal -fit_fm2v3_rh_supramarginal_cor <- cfa(fm2v3_rh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_supramarginal_cor <- cfa(fm1v3_rh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_supramarginal_cor <- cfa(sr1_rh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_supramarginal_cor <- cfa(sr2_rh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_supramarginal_cor <- cfa(hm1_rh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_supramarginal_cor <- cfa(hm2_rh_supramarginal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_supramarginal_corage <- cfa(fm2v3_rh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_supramarginal_corage <- cfa(fm1v3_rh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_supramarginal_corage <- cfa(sr1_rh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_supramarginal_corage <- cfa(sr2_rh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_supramarginal_corage <- cfa(hm1_rh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_supramarginal_corage <- cfa(hm2_rh_supramarginal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_supramarginal -summary(fit_fm2v3_rh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_supramarginal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_supramarginal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_supramarginal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_supramarginal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_frontalpole -fit_fm2v3_rh_frontalpole_cor <- cfa(fm2v3_rh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_frontalpole_cor <- cfa(fm1v3_rh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_frontalpole_cor <- cfa(sr1_rh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_frontalpole_cor <- cfa(sr2_rh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_frontalpole_cor <- cfa(hm1_rh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_frontalpole_cor <- cfa(hm2_rh_frontalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_frontalpole_corage <- cfa(fm2v3_rh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_frontalpole_corage <- cfa(fm1v3_rh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_frontalpole_corage <- cfa(sr1_rh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_frontalpole_corage <- cfa(sr2_rh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_frontalpole_corage <- cfa(hm1_rh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_frontalpole_corage <- cfa(hm2_rh_frontalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_frontalpole -summary(fit_fm2v3_rh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_frontalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_frontalpole_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_frontalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_frontalpole_corage, fit.measures = T, standardized = T) - -# Fit models - rh_temporalpole -fit_fm2v3_rh_temporalpole_cor <- cfa(fm2v3_rh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_temporalpole_cor <- cfa(fm1v3_rh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_temporalpole_cor <- cfa(sr1_rh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_temporalpole_cor <- cfa(sr2_rh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_temporalpole_cor <- cfa(hm1_rh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_temporalpole_cor <- cfa(hm2_rh_temporalpole_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_temporalpole_corage <- cfa(fm2v3_rh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_temporalpole_corage <- cfa(fm1v3_rh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_temporalpole_corage <- cfa(sr1_rh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_temporalpole_corage <- cfa(sr2_rh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_temporalpole_corage <- cfa(hm1_rh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_temporalpole_corage <- cfa(hm2_rh_temporalpole_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_temporalpole -summary(fit_fm2v3_rh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_temporalpole_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_temporalpole_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_temporalpole_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_temporalpole_corage, fit.measures = T, standardized = T) - -# Fit models - rh_transversetemporal -fit_fm2v3_rh_transversetemporal_cor <- cfa(fm2v3_rh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_transversetemporal_cor <- cfa(fm1v3_rh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_transversetemporal_cor <- cfa(sr1_rh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_transversetemporal_cor <- cfa(sr2_rh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_transversetemporal_cor <- cfa(hm1_rh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_transversetemporal_cor <- cfa(hm2_rh_transversetemporal_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_transversetemporal_corage <- cfa(fm2v3_rh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_transversetemporal_corage <- cfa(fm1v3_rh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_transversetemporal_corage <- cfa(sr1_rh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_transversetemporal_corage <- cfa(sr2_rh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_transversetemporal_corage <- cfa(hm1_rh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_transversetemporal_corage <- cfa(hm2_rh_transversetemporal_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_transversetemporal -summary(fit_fm2v3_rh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr1_rh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_sr2_rh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm1_rh_transversetemporal_cor, fit.measures = T, standardized = T) -summary(fit_hm2_rh_transversetemporal_cor, fit.measures = T, standardized = T) - -summary(fit_fm2v3_rh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_transversetemporal_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_transversetemporal_corage, fit.measures = T, standardized = T) - -# Fit models - rh_insula -fit_fm2v3_rh_insula_cor <- cfa(fm2v3_rh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_insula_cor <- cfa(fm1v3_rh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_insula_cor <- cfa(sr1_rh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_insula_cor <- cfa(sr2_rh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_insula_cor <- cfa(hm1_rh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_insula_cor <- cfa(hm2_rh_insula_cor, data = data, estimator = "ML", - missing = "ML", verbose = T) - -fit_fm2v3_rh_insula_corage <- cfa(fm2v3_rh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_fm1v3_rh_insula_corage <- cfa(fm1v3_rh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr1_rh_insula_corage <- cfa(sr1_rh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_sr2_rh_insula_corage <- cfa(sr2_rh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm1_rh_insula_corage <- cfa(hm1_rh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) -fit_hm2_rh_insula_corage <- cfa(hm2_rh_insula_corage, data = data_age2, estimator = "ML", - missing = "ML", verbose = T) - -# Summary Stats for models - rh_insula summary(fit_fm2v3_rh_insula_cor, fit.measures = T, standardized = T) summary(fit_fm1v3_rh_insula_cor, fit.measures = T, standardized = T) summary(fit_sr1_rh_insula_cor, fit.measures = T, standardized = T) @@ -20328,12 +12025,6 @@ summary(fit_sr2_rh_insula_cor, fit.measures = T, standardized = T) summary(fit_hm1_rh_insula_cor, fit.measures = T, standardized = T) summary(fit_hm2_rh_insula_cor, fit.measures = T, standardized = T) -summary(fit_fm2v3_rh_insula_corage, fit.measures = T, standardized = T) -summary(fit_fm1v3_rh_insula_corage, fit.measures = T, standardized = T) -summary(fit_sr1_rh_insula_corage, fit.measures = T, standardized = T) -summary(fit_sr2_rh_insula_corage, fit.measures = T, standardized = T) -summary(fit_hm1_rh_insula_corage, fit.measures = T, standardized = T) -summary(fit_hm2_rh_insula_corage, fit.measures = T, standardized = T) ```