Causal Decomposition Analysis R package causal.decomp version 0.2.0 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>. Software 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 Suyeon Kang <suyeon.kang@ucf.edu> Comprehensive R Archive Network (CRAN) Suyeon Kang [aut, cre], Soojin Park [aut], Karen Xu [ctb] GPL-2 2025-08-27 application/tgz https://CRAN.R-project.org/package=causal.decomp doi:10.32614/CRAN.package.causal.decomp en-US