brmsmargins: Bayesian Marginal Effects for 'brms' Models

Calculate Bayesian marginal effects and average marginal effects 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>).

Version: 0.1.1
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: 2021-12-16
Author: Joshua F. Wiley ORCID iD [aut, cre]
Maintainer: Joshua F. Wiley <jwiley.psych at gmail.com>
BugReports: https://github.com/JWiley/brmsmargins/issues
License: GPL (≥ 3)
URL: https://joshuawiley.com/brmsmargins/, https://github.com/JWiley/brmsmargins
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: brmsmargins results

Documentation:

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

Downloads:

Package source: brmsmargins_0.1.1.tar.gz
Windows binaries: r-devel: brmsmargins_0.1.1.zip, r-release: brmsmargins_0.1.1.zip, r-oldrel: brmsmargins_0.1.1.zip
macOS binaries: r-release (arm64): brmsmargins_0.1.1.tgz, r-release (x86_64): brmsmargins_0.1.1.tgz, r-oldrel: brmsmargins_0.1.1.tgz

Linking:

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