Package: bama
Title: High Dimensional Bayesian Mediation Analysis
Version: 1.3.0
URL: https://github.com/umich-cphds/bama
BugReports: https://github.com/umich-cphds/bama/issues
Authors@R: 
    c(person(given = "Alexander",
           family = "Rix",
           role = c("aut"),
           email = "alexrix@umich.edu"),
      person(given = "Mike",
           family = "Kleinsasser",
           role = c("aut", "cre"),
           email = "mkleinsa@umich.edu"),
      person(given = "Yanyi",
           family = "Song",
           role = c("aut"),
           email = "yanys@umich.edu"))
Description: 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.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
LinkingTo: Rcpp, RcppArmadillo, RcppDist, BH
Imports: Rcpp, parallel
Depends: R (>= 3.5)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2023-01-24 17:46:06 UTC; mk
Author: Alexander Rix [aut],
  Mike Kleinsasser [aut, cre],
  Yanyi Song [aut]
Maintainer: Mike Kleinsasser <mkleinsa@umich.edu>
Repository: CRAN
Date/Publication: 2023-01-24 18:10:02 UTC
Built: R 4.2.0; aarch64-apple-darwin20; 2023-04-10 22:19:50 UTC; unix
Archs: bama.so.dSYM
