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) and
Song et al (2020) ,
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.