hdbma-package: Bayesian Mediation Analysis with High-Dimensional Data

hdbma-packageR Documentation

Bayesian Mediation Analysis with High-Dimensional Data

Description

Mediation analysis is used to identify and quantify intermediate effects from factors that intervene the observed relationship between an exposure/predicting variable and an outcome. We use a Bayesian adaptive lasso method to take care of the hierarchical structures and high dimensional exposures or mediators.

Details

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The main function is hdbma to perform the Bayesian mediation anlysis with adaptive Laplace priors.

Author(s)

Qingzhao Yu [aut, cre, cph], Bin Li [aut]

Maintainer: Qingzhao Yu <qyu@lsuhsc.edu>

References

Yu, Q., Hagan, J., Wu, X., Richmond-Bryant, J., and Li, B., 2023, High-Dimensional Bayesian Mediation Analysis with Adaptive Laplace Priors. Submitted.

Examples

#See examples at summary.hdbma.

hdbma documentation built on May 29, 2024, 11:17 a.m.