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) <doi:10.1111/j.2041-210x.2012.00261.x> and
Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>.
| Version: |
0.9.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
methods, stats, lme4 (≥ 1.1-21), pbapply (≥ 1.4-2), dplyr (≥ 0.8.3), 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: |
2021-01-18 |
| 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 |
| CRAN checks: |
partR2 results |