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hdbm  

High Dimensional Bayesian Mediation Analysis
View on CRAN: Click here


Download and install hdbm package within the R console
Install from CRAN:
install.packages("hdbm")

Install from Github:
library("remotes")
install_github("cran/hdbm")

Install by package version:
library("remotes")
install_version("hdbm", "0.9.0")



Attach the package and use:
library("hdbm")
Maintained by
Alexander Rix
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-28
Latest Update: 2019-08-28
Description:
Perform mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. High dimensional Bayesian mediation (HDBM), developed by Song et al (2018) , 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.
How to cite:
Alexander Rix (2019). hdbm: High Dimensional Bayesian Mediation Analysis. R package version 0.9.0, https://cran.r-project.org/web/packages/hdbm. Accessed 21 Nov. 2024.
Previous versions and publish date:
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Complete documentation for hdbm
Functions, R codes and Examples using the hdbm R package
Some associated functions: hdbm.data . hdbm . 
Some associated R codes: RcppExports.R . data.R . hdbm.R .  Full hdbm package functions and examples
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