bama: High Dimensional Bayesian Mediation Analysis (original) (raw)
Perform mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. Bayesian Mediation Analysis (BAMA), developed by Song et al (2019) <doi:10.1111/biom.13189> and Song et al (2020) <doi:10.48550/arXiv.2009.11409>, relies on two Bayesian sparse linear mixed models to simultaneously analyze a relatively large number of mediators for a continuous exposure and outcome assuming a small number of mediators are truly active. This sparsity assumption also allows the extension of univariate mediator analysis by casting the identification of active mediators as a variable selection problem and applying Bayesian methods with continuous shrinkage priors on the effects.
| Version: | 1.3.1 |
|---|---|
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp, parallel |
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist, BH |
| Suggests: | knitr, rmarkdown |
| Published: | 2025-09-20 |
| DOI: | 10.32614/CRAN.package.bama |
| Author: | Alexander Rix [aut], Mike Kleinsasser [aut, cre], Yanyi Song [aut] |
| Maintainer: | Mike Kleinsasser |
| BugReports: | https://github.com/umich-cphds/bama/issues |
| License: | GPL-3 |
| URL: | https://github.com/umich-cphds/bama |
| NeedsCompilation: | yes |
| Materials: | README |
| In views: | Bayesian |
| CRAN checks: | bama results |
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