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rmpw
View on CRAN: Click
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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
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[Scholar Profile | Author Map]
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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 15 Jul. 2026.
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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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