causal.decomp: Causal Decomposition Analysis
We implement causal decomposition analysis using methods proposed by Park, Lee, and Qin (2022) and Park, Kang, and Lee (2023), which provide researchers with multiple-mediator imputation, single-mediator imputation, and product-of-coefficients regression approaches to estimate the initial disparity, disparity reduction, and disparity remaining (<doi:10.1177/00491241211067516>; <doi:10.1177/00811750231183711>). We also implement sensitivity analysis for causal decomposition using R-squared values as sensitivity parameters (Park, Kang, Lee, and Ma, 2023 <doi:10.1515/jci-2022-0031>). Finally, we include individualized causal decomposition and sensitivity analyses proposed by Park, Kang, and Lee (2025+) <doi:10.48550/arXiv.2506.19010>.
| Version: |
0.2.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
stats, parallel, MASS, nnet, SuppDists, PSweight, utils, rlang, DynTxRegime, distr, rpart, dplyr, modelObj, magrittr, knitr |
| Suggests: |
rmarkdown, rpart.plot, spelling, CBPS, pbmcapply |
| Published: |
2025-08-27 |
| Author: |
Suyeon Kang [aut, cre],
Soojin Park [aut],
Karen Xu [ctb] |
| Maintainer: |
Suyeon Kang <suyeon.kang at ucf.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Language: |
en-US |
| CRAN checks: |
causal.decomp results |
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