Package: hdbm 0.9.0
Alexander Rix
hdbm: High Dimensional Bayesian Mediation Analysis
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) <doi:10.1101/467399>, 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:
hdbm_0.9.0.tar.gz
hdbm_0.9.0.tar.gz(r-4.5-noble)hdbm_0.9.0.tar.gz(r-4.4-noble)
hdbm_0.9.0.tgz(r-4.4-emscripten)hdbm_0.9.0.tgz(r-4.3-emscripten)
hdbm.pdf |hdbm.html✨
hdbm/json (API)
NEWS
# Install 'hdbm' in R: |
install.packages('hdbm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- hdbm.data - Synthetic example data for hdbm
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:deea44438f. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 17 2024 |
R-4.5-linux-x86_64 | NOTE | Oct 17 2024 |
Exports:hdbm
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
High Dimensional Bayesian Mediation | hdbm |
Synthetic example data for hdbm | hdbm.data |