partR2: Partitioning R2 in GLMMs

Partitioning the R2 of GLMMs into variation explained by each predictor and combination of predictors using semi-partial (part) R2 and inclusive R2. Methods are based on the R2 for GLMMs described in Nakagawa & Schielzeth (2013) and Nakagawa, Johnson & Schielzeth (2017).

Version: 0.9.2
Depends: R (≥ 3.5.0)
Imports: methods, stats, lme4 (≥ 1.1-21), pbapply (≥ 1.4-2), dplyr (≥ 1.0.0), purrr (≥ 0.3.3), rlang (≥ 0.4.2), tibble (≥ 2.1.3), magrittr (≥ 1.5), ggplot2 (≥ 3.3.0), tidyr (≥ 1.1)
Suggests: testthat, future, furrr, knitr, rmarkdown, patchwork, covr
Published: 2024-03-04
DOI: 10.32614/CRAN.package.partR2
Author: Martin A. Stoffel [aut, cre], Shinichi Nakagawa [aut], Holger Schielzeth [aut]
Maintainer: Martin A. Stoffel <martin.adam.stoffel at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: partR2 citation info
Materials: README NEWS
In views: MixedModels
CRAN checks: partR2 results


Reference manual: partR2.pdf
Vignettes: Using partR2


Package source: partR2_0.9.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): partR2_0.9.2.tgz, r-oldrel (arm64): partR2_0.9.2.tgz, r-release (x86_64): partR2_0.9.2.tgz, r-oldrel (x86_64): partR2_0.9.2.tgz
Old sources: partR2 archive


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