bama: High Dimensional Bayesian Mediation Analysis

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) <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: 1.2
Depends: R (≥ 3.5)
Imports: Rcpp, parallel
LinkingTo: Rcpp, RcppArmadillo, RcppDist, BH
Suggests: knitr, rmarkdown
Published: 2021-01-21
Author: Alexander Rix [aut], Mike Kleinsasser [aut, cre], Yanyi Song [aut]
Maintainer: Mike Kleinsasser <mkleinsa at>
License: GPL-3
NeedsCompilation: yes
Materials: README
In views: Bayesian
CRAN checks: bama results


Reference manual: bama.pdf
Vignettes: Bayesian Mediation Analysis in R


Package source: bama_1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bama_1.2.tgz, r-release (x86_64): bama_1.2.tgz, r-oldrel: bama_1.2.tgz
Old sources: bama archive


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