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>, 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: | 1.0.1 |
Depends: | R (≥ 3.5) |
Imports: | Rcpp, parallel |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | knitr, rmarkdown |
Published: | 2020-05-02 |
Author: | Alexander Rix [aut, cre], Yanyi Song [aut] |
Maintainer: | Alexander Rix <alexrix at umich.edu> |
BugReports: | https://github.com/umich-cphds/bama/issues |
License: | GPL-3 |
URL: | https://github.com/umich-cphds/bama |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | bama results |
Reference manual: | bama.pdf |
Vignettes: |
Bayesian Mediation Analysis in R |
Package source: | bama_1.0.1.tar.gz |
Windows binaries: | r-devel: bama_1.0.1.zip, r-release: bama_1.0.1.zip, r-oldrel: bama_1.0.1.zip |
macOS binaries: | r-release: bama_1.0.1.tgz, r-oldrel: bama_1.0.1.tgz |
Old sources: | bama archive |
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