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rmpw  

Causal Mediation Analysis Using Weighting Approach
View on CRAN: Click here


Download and install rmpw package within the R console
Install from CRAN:
install.packages("rmpw")

Install from Github:
library("remotes")
install_github("cran/rmpw")

Install by package version:
library("remotes")
install_version("rmpw", "0.0.6")



Attach the package and use:
library("rmpw")
Maintained by
Xu Qin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-02-27
Latest Update: 2024-03-06
Description:
We implement causal mediation analysis using the methods proposed by Hong (2010) and Hong, Deutsch & Hill (2015) . It allows the estimation and hypothesis testing of causal mediation effects through ratio of mediator probability weights (RMPW). This strategy conveniently relaxes the assumption of no treatment-by-mediator interaction while greatly simplifying the outcome model specification without invoking strong distributional assumptions. We also implement a sensitivity analysis by extending the RMPW method to assess potential bias in the presence of omitted pretreatment or posttreatment covariates. The sensitivity analysis strategy was proposed by Hong, Qin, and Yang (2018) .
How to cite:
Xu Qin (2017). rmpw: Causal Mediation Analysis Using Weighting Approach. R package version 0.0.6, https://cran.r-project.org/web/packages/rmpw. Accessed 28 Oct. 2026.
Previous versions and publish date:
(2026-10-01 10:40), 0.0.1 (2017-02-27 10:05), 0.0.2 (2017-12-21 22:16), 0.0.3 (2018-01-04 16:44), 0.0.4 (2018-07-18 15:40), 0.0.5 (2024-03-06 05:50), 0.0.6 (2025-11-17 17:10)
Other packages that cited rmpw R package
View rmpw citation profile
Other R packages that rmpw depends, imports, suggests or enhances
Complete documentation for rmpw
Functions, R codes and Examples using the rmpw R package
Some associated functions: Riverside . rmpw . sensitivity . sensitivity.plot . 
Some associated R codes: rmpw.R .  Full rmpw package functions and examples
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