bayesMeanScale: Bayesian Post-Estimation on the Mean Scale

Computes Bayesian posterior distributions of predictions, marginal effects, and differences of marginal effects for various generalized linear models. Importantly, the posteriors are on the mean (response) scale, allowing for more natural interpretation than summaries on the link scale. Also, predictions and marginal effects of the count probabilities for Poisson and negative binomial models can be computed.

Version: 0.1.4
Depends: R (≥ 3.5.0)
Imports: bayestestR (≥ 0.13.2), data.table (≥ 1.15.2), magrittr (≥ 2.0.3), posterior (≥ 1.5.0)
Suggests: flextable (≥ 0.9.5), knitr (≥ 1.45), rmarkdown (≥ 2.26), rstanarm (≥ 2.32.1), testthat (≥ 3.0.0)
Published: 2024-05-30
DOI: 10.32614/CRAN.package.bayesMeanScale
Author: David M. Dalenberg [aut, cre]
Maintainer: David M. Dalenberg <dalenbe2 at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: bayesMeanScale results


Reference manual: bayesMeanScale.pdf
Vignettes: Introduction to 'bayesMeanScale'


Package source: bayesMeanScale_0.1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bayesMeanScale_0.1.4.tgz, r-oldrel (arm64): bayesMeanScale_0.1.4.tgz, r-release (x86_64): bayesMeanScale_0.1.4.tgz, r-oldrel (x86_64): bayesMeanScale_0.1.4.tgz
Old sources: bayesMeanScale archive


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