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BaHZING: Bayesian Hierarchical Zero-Inflated Negative Binomial Regression
with 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 Goodrich 
[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:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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