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)
Published:
2025年02月17日
Author:
Hailey Hampson [aut],
Jesse Goodrich
ORCID iD
[aut, cre],
Hongxu Wang [aut],
Tanya Alderete [ctb],
Shardul Nazirkar [ctb],
David Conti [aut]
Maintainer:
Jesse Goodrich <jagoodri at usc.edu>
NeedsCompilation:
no
SystemRequirements:
JAGS 4.x.y (http://mcmc-jags.sourceforge.net)
Documentation:
Downloads:
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