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add cran link
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krisrs1128 committed Sep 19, 2024
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6 changes: 6 additions & 0 deletions README.Rmd
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Expand Up @@ -37,6 +37,12 @@ a mindfulness intervention study.

## Installation

You can install the stable [CRAN version](https://cran.r-project.org/package=multimedia) with:

``` r
install.packages("multimedia")
```

You can install the development version from
[GitHub](https://github.com/krisrs1128/multimedia) with:

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181 changes: 34 additions & 147 deletions README.md
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Expand Up @@ -31,6 +31,11 @@ and survey responses in a mindfulness intervention study.

## Installation

You can install the stable [CRAN
version](https://cran.r-project.org/package=multimedia) with:

install.packages("multimedia")

You can install the development version from
[GitHub](https://github.com/krisrs1128/multimedia) with:

Expand Down Expand Up @@ -106,22 +111,16 @@ are identical for the two indirect settings.

direct_effect(model, exper)

<pre class="r-output"><code>## outcome indirect_setting
## 1 PHQ Control
## 2 PHQ Treatment
## contrast direct_effect
## 1 Control - Treatment 0.09314376
## 2 Control - Treatment 0.09314376
<pre class="r-output"><code>## outcome indirect_setting contrast direct_effect
## 1 PHQ Control Control - Treatment 0.09314376
## 2 PHQ Treatment Control - Treatment 0.09314376
</code></pre>

indirect_overall(model, exper)

<pre class="r-output"><code>## outcome direct_setting contrast
## 1 PHQ Control Control - Treatment
## 2 PHQ Treatment Control - Treatment
## indirect_effect
## 1 0.02256029
## 2 0.02256029
<pre class="r-output"><code>## outcome direct_setting contrast indirect_effect
## 1 PHQ Control Control - Treatment 0.02256029
## 2 PHQ Treatment Control - Treatment 0.02256029
</code></pre>

The package also includes helpers to visualize and perform inference on
Expand All @@ -146,12 +145,9 @@ model, which correctly recovers that the direct effects are 0.
estimate(exper) |>
direct_effect()

<pre class="r-output"><code>## outcome indirect_setting
## 1 PHQ Control
## 2 PHQ Treatment
## contrast direct_effect
## 1 Control - Treatment 0
## 2 Control - Treatment 0
<pre class="r-output"><code>## outcome indirect_setting contrast direct_effect
## 1 PHQ Control Control - Treatment 0
## 2 PHQ Treatment Control - Treatment 0
</code></pre>

## Help
Expand All @@ -177,137 +173,28 @@ We welcome questions and comments about the package either through
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils
## [5] datasets methods base
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggplot2_3.5.1 multimedia_0.2.0
## [3] tidyselect_1.2.1 ranger_0.16.0
## [5] glmnetUtils_1.1.9 brms_2.21.0
## [7] Rcpp_1.0.13
## [1] ggplot2_3.5.1 multimedia_0.2.0 tidyselect_1.2.1 ranger_0.16.0 glmnetUtils_1.1.9 brms_2.21.0 Rcpp_1.0.13
##
## loaded via a namespace (and not attached):
## [1] gridExtra_2.3
## [2] inline_0.3.19
## [3] permute_0.9-7
## [4] sandwich_3.1-0
## [5] rlang_1.1.4
## [6] magrittr_2.0.3
## [7] multcomp_1.4-26
## [8] ade4_1.7-22
## [9] matrixStats_1.4.1
## [10] compiler_4.4.1
## [11] mgcv_1.9-1
## [12] loo_2.8.0
## [13] vctrs_0.6.5
## [14] reshape2_1.4.4
## [15] stringr_1.5.1
## [16] pkgconfig_2.0.3
## [17] shape_1.4.6.1
## [18] crayon_1.5.3
## [19] fastmap_1.2.0
## [20] backports_1.5.0
## [21] XVector_0.45.0
## [22] labeling_0.4.3
## [23] utf8_1.2.4
## [24] rmarkdown_2.28
## [25] UCSC.utils_1.1.0
## [26] purrr_1.0.2
## [27] xfun_0.47
## [28] glmnet_4.1-8
## [29] zlibbioc_1.51.1
## [30] GenomeInfoDb_1.41.1
## [31] jsonlite_1.8.8
## [32] progress_1.2.3
## [33] biomformat_1.33.0
## [34] highr_0.11
## [35] rhdf5filters_1.17.0
## [36] DelayedArray_0.31.11
## [37] Rhdf5lib_1.27.0
## [38] prettyunits_1.2.0
## [39] cluster_2.1.6
## [40] parallel_4.4.1
## [41] R6_2.5.1
## [42] stringi_1.8.4
## [43] StanHeaders_2.32.10
## [44] GenomicRanges_1.57.1
## [45] estimability_1.5.1
## [46] rstan_2.32.6
## [47] SummarizedExperiment_1.35.1
## [48] iterators_1.0.14
## [49] knitr_1.48
## [50] zoo_1.8-12
## [51] IRanges_2.39.2
## [52] bayesplot_1.11.1
## [53] igraph_2.0.3
## [54] Matrix_1.7-0
## [55] splines_4.4.1
## [56] abind_1.4-5
## [57] yaml_2.3.10
## [58] vegan_2.6-8
## [59] codetools_0.2-20
## [60] curl_5.2.2
## [61] pkgbuild_1.4.4
## [62] lattice_0.22-6
## [63] tibble_3.2.1
## [64] plyr_1.8.9
## [65] withr_3.0.1
## [66] Biobase_2.65.1
## [67] bridgesampling_1.1-2
## [68] posterior_1.6.0
## [69] coda_0.19-4.1
## [70] evaluate_0.24.0
## [71] survival_3.7-0
## [72] RcppParallel_5.1.9
## [73] Biostrings_2.73.1
## [74] pillar_1.9.0
## [75] phyloseq_1.49.0
## [76] MatrixGenerics_1.17.0
## [77] tensorA_0.36.2.1
## [78] checkmate_2.3.2
## [79] foreach_1.5.2
## [80] stats4_4.4.1
## [81] distributional_0.4.0
## [82] generics_0.1.3
## [83] hms_1.1.3
## [84] S4Vectors_0.43.2
## [85] rstantools_2.4.0
## [86] munsell_0.5.1
## [87] scales_1.3.0
## [88] xtable_1.8-4
## [89] glue_1.7.0
## [90] emmeans_1.10.4
## [91] tools_4.4.1
## [92] data.table_1.16.0
## [93] mvtnorm_1.3-1
## [94] tidygraph_1.3.1
## [95] rhdf5_2.49.0
## [96] grid_4.4.1
## [97] tidyr_1.3.1
## [98] ape_5.8
## [99] QuickJSR_1.3.1
## [100] miniLNM_0.1.0
## [101] colorspace_2.1-1
## [102] nlme_3.1-166
## [103] formula.tools_1.7.1
## [104] GenomeInfoDbData_1.2.12
## [105] patchwork_1.2.0
## [106] cli_3.6.3
## [107] fansi_1.0.6
## [108] S4Arrays_1.5.7
## [109] Brobdingnag_1.2-9
## [110] dplyr_1.1.4
## [111] V8_5.0.0
## [112] gtable_0.3.5
## [113] digest_0.6.37
## [114] operator.tools_1.6.3
## [115] BiocGenerics_0.51.1
## [116] SparseArray_1.5.31
## [117] TH.data_1.1-2
## [118] farver_2.1.2
## [119] multtest_2.61.0
## [120] htmltools_0.5.8.1
## [121] lifecycle_1.0.4
## [122] httr_1.4.7
## [123] MASS_7.3-61
## [1] tensorA_0.36.2.1 jsonlite_1.8.8 shape_1.4.6.1 magrittr_2.0.3 TH.data_1.1-2 estimability_1.5.1 farver_2.1.2 rmarkdown_2.28
## [9] fs_1.6.4 zlibbioc_1.51.1 vctrs_0.6.5 multtest_2.61.0 memoise_2.0.1 progress_1.2.3 htmltools_0.5.8.1 S4Arrays_1.5.7
## [17] usethis_3.0.0 distributional_0.5.0 curl_5.2.2 Rhdf5lib_1.27.0 SparseArray_1.5.31 rhdf5_2.49.0 StanHeaders_2.32.10 htmlwidgets_1.6.4
## [25] plyr_1.8.9 sandwich_3.1-0 emmeans_1.10.4 zoo_1.8-12 cachem_1.1.0 igraph_2.0.3 mime_0.12 lifecycle_1.0.4
## [33] iterators_1.0.14 pkgconfig_2.0.3 Matrix_1.7-0 R6_2.5.1 fastmap_1.2.0 GenomeInfoDbData_1.2.12 MatrixGenerics_1.17.0 shiny_1.9.1
## [41] digest_0.6.37 colorspace_2.1-1 patchwork_1.3.0 S4Vectors_0.43.2 pkgload_1.4.0 miniLNM_0.1.0 GenomicRanges_1.57.1 vegan_2.6-8
## [49] labeling_0.4.3 fansi_1.0.6 mgcv_1.9-1 httr_1.4.7 abind_1.4-8 compiler_4.4.1 remotes_2.5.0 withr_3.0.1
## [57] backports_1.5.0 inline_0.3.19 highr_0.11 QuickJSR_1.3.1 pkgbuild_1.4.4 MASS_7.3-61 DelayedArray_0.31.11 sessioninfo_1.2.2
## [65] biomformat_1.33.0 permute_0.9-7 loo_2.8.0 tools_4.4.1 ape_5.8 httpuv_1.6.15 glue_1.7.0 rhdf5filters_1.17.0
## [73] nlme_3.1-166 promises_1.3.0 grid_4.4.1 checkmate_2.3.2 cluster_2.1.6 reshape2_1.4.4 ade4_1.7-22 generics_0.1.3
## [81] operator.tools_1.6.3 gtable_0.3.5 formula.tools_1.7.1 tidyr_1.3.1 hms_1.1.3 data.table_1.16.0 tidygraph_1.3.1 utf8_1.2.4
## [89] XVector_0.45.0 BiocGenerics_0.51.1 foreach_1.5.2 pillar_1.9.0 stringr_1.5.1 posterior_1.6.0 later_1.3.2 splines_4.4.1
## [97] dplyr_1.1.4 lattice_0.22-6 survival_3.7-0 Biostrings_2.73.1 miniUI_0.1.1.1 knitr_1.48 gridExtra_2.3 V8_5.0.0
## [105] phyloseq_1.49.0 IRanges_2.39.2 SummarizedExperiment_1.35.1 stats4_4.4.1 xfun_0.47 bridgesampling_1.1-2 Biobase_2.65.1 devtools_2.4.5
## [113] matrixStats_1.4.1 rstan_2.32.6 stringi_1.8.4 UCSC.utils_1.1.0 yaml_2.3.10 evaluate_0.24.0 codetools_0.2-20 tibble_3.2.1
## [121] cli_3.6.3 RcppParallel_5.1.9 xtable_1.8-4 munsell_0.5.1 GenomeInfoDb_1.41.1 coda_0.19-4.1 parallel_4.4.1 rstantools_2.4.0
## [129] ellipsis_0.3.2 prettyunits_1.2.0 profvis_0.3.8 urlchecker_1.0.1 bayesplot_1.11.1 Brobdingnag_1.2-9 glmnet_4.1-8 mvtnorm_1.3-1
## [137] scales_1.3.0 purrr_1.0.2 crayon_1.5.3 rlang_1.1.4 multcomp_1.4-26
</code></pre>

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