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BaHZING: Bayesian Hierarchical Zero-Inflated Negative Binomial Regressionwith G-Computation

A Bayesian model for examining the association between environmental mixtures and all Taxa measured in a hierarchical microbiome dataset in a single integrated analysis. Compared with analyzing the associations of environmental mixtures with each Taxa individually, 'BaHZING' controls Type 1 error rates and provides more stable effect estimates when dealing with small sample sizes.

Version:1.0.0
Depends:R (≥ 4.1.0),rjags (≥ 4.0.0)
Imports:bayestestR,dplyr,magrittr,phyloseq,pscl,R2jags, stats,stringr,tidyr
Suggests:testthat (≥ 3.0.0)
Published:2025-02-17
DOI:10.32614/CRAN.package.BaHZING
Author:Hailey Hampson [aut], Jesse GoodrichORCID iD [aut, cre], Hongxu Wang [aut], Tanya Alderete [ctb], Shardul Nazirkar [ctb], David Conti [aut]
Maintainer:Jesse Goodrich <jagoodri at usc.edu>
License:GPL (≥ 3)
NeedsCompilation:no
SystemRequirements:JAGS 4.x.y (http://mcmc-jags.sourceforge.net)
Materials:README,NEWS
CRAN checks:BaHZING results

Documentation:

Reference manual:BaHZING.html ,BaHZING.pdf

Downloads:

Package source: BaHZING_1.0.0.tar.gz
Windows binaries: r-devel:BaHZING_1.0.0.zip, r-release:BaHZING_1.0.0.zip, r-oldrel:BaHZING_1.0.0.zip
macOS binaries: r-release (arm64):BaHZING_1.0.0.tgz, r-oldrel (arm64):BaHZING_1.0.0.tgz, r-release (x86_64):BaHZING_1.0.0.tgz, r-oldrel (x86_64):BaHZING_1.0.0.tgz

Linking:

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