partR2: Partitioning R2 in GLMMs (original) (raw)
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 gmail.com> |
| BugReports: | https://github.com/mastoffel/partR2/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/mastoffel/partR2 |
| NeedsCompilation: | no |
| Citation: | partR2 citation info |
| Materials: | README NEWS |
| In views: | MixedModels |
| CRAN checks: | partR2 results |
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