Update docs, site

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: interactions
 Type: Package
 Title: Comprehensive, User-Friendly Toolkit for Probing Interactions
-Version: 1.0.0.9000
+Version: 1.0.0
 Authors@R: person(c("Jacob","A."), "Long", email = "[email protected]",
   role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1582-6214"))
 Description: A suite of functions for conducting and interpreting analysis 
@@ -39,4 +39,3 @@ Suggests:
 RoxygenNote: 6.1.1
 VignetteBuilder: knitr
 Roxygen: list(markdown = TRUE)
-Remotes: jacob-long/jtools@interactions-split

NEWS.md

@@ -25,6 +25,7 @@ their usage.
 caused RStudio notebook users issues with the output not being printed to the
 console and having the notebook format them in less-than-ideal ways. The tables
 now have a markdown format that might remind you of Stata's coefficient tables.
+Thanks to Kim Henry for contacting me about this.
 
 ## Use partial residuals for plotting 
 

README.Rmd

@@ -43,22 +43,18 @@ Quick rundown of features:
 All of these are implemented in a consistent interface designed to be as
 simple as possible with tweaks and guts available to advanced users. 
 GLMs, models from the `survey` package, and multilevel models from `lme4`
-are fully supported as are visualization for Bayesian models from `rstanaram` 
+are fully supported as is visualization for Bayesian models from `rstanaram` 
 and `brms`.
 
 
 ## Installation
 
-For the moment, the package is not yet on CRAN and you must 
-install from Github. Because it depends on a not-yet-released version of 
-`jtools`, you will also need to grab it from Github first.
+For the moment, the package has just been submitted to CRAN and may not yet
+be available as you read this. If that is the case, please
+install from Github.
 
 ```r
-if (!requireNamespace("devtools", quietly = TRUE)) {
-  install.packages("devtools")
-}
-devtools::install_github("jacob-long/jtools", ref = "interactions-split")
-devtools::install_github("jacob-long/interactions")
+source("https://install-github.me/jacob-long/interactions")
 ```
 
 ## Usage
@@ -129,7 +125,10 @@ categorical interactions can be investigated using the `cat_plot` function.
 
 ## Contributing
 
-I'm happy to receive bug reports, suggestions, questions, and (most of all) contributions to fix problems and add features. I prefer you use the Github issues system over trying to reach out to me in other ways. Pull requests for contributions are encouraged.
+I'm happy to receive bug reports, suggestions, questions, and (most of all) 
+contributions to fix problems and add features. I prefer you use the Github 
+issues system over trying to reach out to me in other ways. Pull requests for
+contributions are encouraged.
 
 Please note that this project is released with a 
 [Contributor Code of Conduct](CONDUCT.md). By participating in this project

README.md

@@ -32,20 +32,16 @@ Quick rundown of features:
 All of these are implemented in a consistent interface designed to be as
 simple as possible with tweaks and guts available to advanced users.
 GLMs, models from the `survey` package, and multilevel models from
-`lme4` are fully supported as are visualization for Bayesian models from
+`lme4` are fully supported as is visualization for Bayesian models from
 `rstanaram` and `brms`.
 
 ## Installation
 
-For the moment, the package is not yet on CRAN and you must install from
-Github. Because it depends on a not-yet-released version of `jtools`,
-you will also need to grab it from Github first.
+For the moment, the package has just been submitted to CRAN and may not
+yet be available as you read this. If that is the case, please install
+from Github.
 
 ``` r
-if (!requireNamespace("devtools", quietly = TRUE)) {
-  install.packages("devtools")
-}
-devtools::install_github("jacob-long/jtools", ref = "interactions-split")
 devtools::install_github("jacob-long/interactions")
 ```
 
@@ -70,7 +66,7 @@ for continuous moderators.
 With that said, the more statistically rigorous way to explore these
 effects is to find the Johnson-Neyman interval, which tells you the
 range of values of the moderator in which the slope of the predictor is
-significant vs. nonsignificant at a specified alpha level.
+significant vs.  nonsignificant at a specified alpha level.
 
 The `sim_slopes` function will by default find the Johnson-Neyman
 interval and tell you the predictor’s slope at specified values of the
@@ -95,16 +91,22 @@ sim_slopes(fiti, pred = hp, modx = wt, jnplot = TRUE)
     #> SIMPLE SLOPES ANALYSIS 
     #> 
     #> Slope of hp when wt = 4.20 (+ 1 SD): 
-    #>   Est. S.E. t val.    p
-    #>  -0.00 0.01  -0.31 0.76
+    #> 
+    #>   Est.   S.E.   t val.      p
+    #> ------  -----  -------  -----
+    #>  -0.00   0.01    -0.31   0.76
     #> 
     #> Slope of hp when wt = 3.22 (Mean): 
-    #>   Est. S.E. t val.    p
-    #>  -0.03 0.01  -4.07 0.00
+    #> 
+    #>   Est.   S.E.   t val.      p
+    #> ------  -----  -------  -----
+    #>  -0.03   0.01    -4.07   0.00
     #> 
     #> Slope of hp when wt = 2.24 (- 1 SD): 
-    #>   Est. S.E. t val.    p
-    #>  -0.06 0.01  -5.66 0.00
+    #> 
+    #>   Est.   S.E.   t val.      p
+    #> ------  -----  -------  -----
+    #>  -0.06   0.01    -5.66   0.00
 
 The Johnson-Neyman plot can really help you get a handle on what the
 interval is telling you, too. Note that you can look at the

_pkgdown.yml

@@ -1,68 +1,9 @@
 template:
   params:
-    bootswatch: flatly
-
-reference:
- - title: Summarizing and visualizing regression models
-   contents:
-    - summ
-    - summ.lm
-    - summ.glm
-    - summ.svyglm
-    - summ.merMod
-    - summ.rq
-    - set_summ_defaults
-    - export_summs
-    - plot_summs
-    - plot_coefs
-    - effect_plot
-    - j_summ
- - title: Probing and visualizing interaction effects
-   contents:
-    - interact_plot
-    - sim_slopes
-    - probe_interaction
-    - johnson_neyman
-    - cat_plot
-    - make_predictions
-    - make_predictions.merMod
-    - make_predictions.rq
-    - make_predictions.brmsfit
-    - make_predictions.stanreg
-    - plot_predictions
-    - as_huxtable.sim_slopes
-    - plot.sim_slopes
- - title: Data centering and scaling tools
-   contents:
-    - gscale
-    - scale_mod
-    - center_mod
-    - standardize
-    - center
- - title: Survey data tools
-   contents:
-    - svycor
-    - svysd
-    - weights_tests
-    - wgttest
-    - pf_sv_test
- - title: Theming
-   contents:
-    - theme_apa
-    - add_gridlines
-    - add_x_gridlines
-    - add_y_gridlines
-    - drop_gridlines
-    - drop_x_gridlines
-    - drop_y_gridlines
- - title: Miscellaneous
-   contents:
-    - jtools_colors
-    - tidy.summ
-    - knit_print.summ.lm
-
+    bootswatch: readable
 
 navbar:
+  type: inverse
   left:
     - icon: fa-home
       href: index.html
@@ -75,16 +16,12 @@ navbar:
     - icon: fa-book
       text: "Vignettes"
       menu:
-      -  text: Tools for summarizing and visualizing regression models
-         href: articles/summ.html
       -  text: Exploring interactions with continuous predictors in regression models
          href: articles/interactions.html
       -  text: Plotting interactions among categorical variables in regression models
          href: articles/categorical.html
-      -  text: Calculate correlations and correlation tables with complex survey data
-         href: articles/svycor.html
+
   right:
     - icon: fa-github fa-lg
       text: "Github"
-      href: https://github.com/jacob-long/jtools
-
+      href: https://github.com/jacob-long/interactions