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 (2018) <doi:10.1101/467399>, 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: | 0.9.1 |
| Imports: | Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2019-09-30 |
| 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: |
High Dimensional Bayesian Mediation Analysis in R |
| Package source: | bama_0.9.1.tar.gz |
| Windows binaries: | r-devel: bama_0.9.1.zip, r-devel-gcc8: bama_0.9.1.zip, r-release: bama_0.9.1.zip, r-oldrel: bama_0.9.1.zip |
| OS X binaries: | r-release: bama_0.9.1.tgz, r-oldrel: bama_0.9.1.tgz |
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