High Dimensional Bayesian Mediation Analysis R package bama version 1.3.1 CRAN Task View: Bayesian (https://CRAN.R-project.org/view=Bayesian) CRAN Task View: CausalInference (https://CRAN.R-project.org/view=CausalInference) 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. Software Depends: R (>= 3.5) Imports: Rcpp, parallel LinkingTo: Rcpp, RcppArmadillo, RcppDist, BH Suggests: knitr, rmarkdown Mike Kleinsasser <mkleinsa@umich.edu> Comprehensive R Archive Network (CRAN) Alexander Rix [aut], Mike Kleinsasser [aut, cre], Yanyi Song [aut] GPL-3 2025-09-20 application/tgz https://CRAN.R-project.org/package=bama doi:10.32614/CRAN.package.bama