Package: rmpw 0.0.5
Xu Qin
rmpw: Causal Mediation Analysis Using Weighting Approach
We implement causal mediation analysis using the methods proposed by Hong (2010) and Hong, Deutsch & Hill (2015) <doi:10.3102/1076998615583902>. 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) <doi:10.3102/1076998617749561>.
Authors:
rmpw_0.0.5.tar.gz
rmpw_0.0.5.tar.gz(r-4.5-noble)rmpw_0.0.5.tar.gz(r-4.4-noble)
rmpw_0.0.5.tgz(r-4.4-emscripten)rmpw_0.0.5.tgz(r-4.3-emscripten)
rmpw.pdf |rmpw.html✨
rmpw/json (API)
| # Install 'rmpw' in R: |
| install.packages('rmpw', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- Riverside - NEWWS Riverside data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 12 months agofrom:19a3d66d8f. Checks:2 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 31 2025 |
| R-4.5-linux | OK | Jan 31 2025 |
Exports:rmpwsensitivitysensitivity.plot
