brmsmargins: Bayesian Marginal Effects for 'brms' Models

Calculate Bayesian marginal effects, average marginal effects, and marginal coefficients (also called population averaged coefficients) for models fit using the 'brms' package including fixed effects, mixed effects, and location scale models. These are based on marginal predictions that integrate out random effects if necessary (see for example <doi:10.1186/s12874-015-0046-6> and <doi:10.1111/biom.12707>).

Version: 0.2.0
Depends: R (≥ 4.0.0)
Imports: methods, stats, data.table (≥ 1.12.0), extraoperators (≥ 0.1.1), brms, bayestestR, Rcpp, posterior
LinkingTo: RcppArmadillo, Rcpp
Suggests: testthat (≥ 3.0.0), covr, withr, knitr, rmarkdown, margins, betareg
Published: 2022-05-18
DOI: 10.32614/CRAN.package.brmsmargins
Author: Joshua F. Wiley ORCID iD [aut, cre], Donald Hedeker ORCID iD [aut]
Maintainer: Joshua F. Wiley <jwiley.psych at>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: brmsmargins results


Reference manual: brmsmargins.pdf
Vignettes: Marginal Effects for Fixed Effects Models
Marginal Effects for Location Scale Models
Marginal Effects for Mixed Effects Models


Package source: brmsmargins_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): brmsmargins_0.2.0.tgz, r-oldrel (arm64): brmsmargins_0.2.0.tgz, r-release (x86_64): brmsmargins_0.2.0.tgz, r-oldrel (x86_64): brmsmargins_0.2.0.tgz
Old sources: brmsmargins archive

Reverse dependencies:

Reverse suggests: marginaleffects


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