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causal.decomp (version 0.2.0)

Causal Decomposition Analysis

Description

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 (; ). We also implement sensitivity analysis for causal decomposition using R-squared values as sensitivity parameters (Park, Kang, Lee, and Ma, 2023 ). Finally, we include individualized causal decomposition and sensitivity analyses proposed by Park, Kang, and Lee (2025+) .

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Version

Install

install.packages('causal.decomp')

Monthly Downloads

258

Version

0.2.0

License

GPL-2

Maintainer

Suyeon Kang

Last Published

August 27th, 2025

Functions in causal.decomp (0.2.0)

smi

Single-Mediator-Imputation Estimation Method
idata

Synthetic Data for illustrating optimal treatment regimes and individualized effects
plot

Visualize sensitivity Objects
causal.decomp-package

causal.decomp: Causal Decomposition Analysis.
ind.sens

Sensitivity Analysis for Causal Decomposition with Individualized Interventions
sensitivity

Sensitivity Analysis Using R-Squared Values for Causal Decomposition Analysis
pocr

Product-of-Coefficients-Regression Estimation Method
mmi

Multiple-Mediator-Imputation Estimation Method
ind.decomp

Causal Decomposition with Individualized Interventions
sMIDUS

Synthetic Data Generated Based on the Midlife Development in the U.S. (MIDUS) Study
sdata

Synthetic Data for Illustration