Package: bama 1.3.0

Mike Kleinsasser

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.

Authors:Alexander Rix [aut], Mike Kleinsasser [aut, cre], Yanyi Song [aut]

bama_1.3.0.tar.gz
bama_1.3.0.tar.gz(r-4.5-noble)bama_1.3.0.tar.gz(r-4.4-noble)
bama_1.3.0.tgz(r-4.4-emscripten)bama_1.3.0.tgz(r-4.3-emscripten)
bama.pdf |bama.html
bama/json (API)

# Install 'bama' in R:
install.packages('bama', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/umich-cphds/bama/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

3.80 score 1 packages 42 scripts 403 downloads 2 exports 4 dependencies

Last updated 2 years agofrom:90fdc67bd4. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKSep 29 2024
R-4.5-linux-x86_64NOTESep 29 2024

Exports:bamafdr.bama

Dependencies:BHRcppRcppArmadilloRcppDist

Bayesian Mediation Analysis in R

Rendered frombama.Rmdusingknitr::rmarkdownon Sep 29 2024.

Last update: 2022-10-20
Started: 2019-09-30