The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The model R squared and semi-partial R squared for the linear and generalized linear mixed model (LMM and GLMM) are computed with confidence limits. The R squared measure from Edwards et.al (2008) <doi:10.1002/sim.3429> is extended to the GLMM using penalized quasi-likelihood (PQL) estimation (see Jaeger et al. 2016 <doi:10.1080/02664763.2016.1193725>). Three methods of computation are provided and described as follows. First, The Kenward-Roger approach. Due to some inconsistency between the 'pbkrtest' package and the 'glmmPQL' function, the Kenward-Roger approach in the 'r2glmm' package is limited to the LMM. Second, The method introduced by Nakagawa and Schielzeth (2013) <doi:10.1111/j.2041-210x.2012.00261.x> and later extended by Johnson (2014) <doi:10.1111/2041-210X.12225>. The 'r2glmm' package only computes marginal R squared for the LMM and does not generalize the statistic to the GLMM; however, confidence limits and semi-partial R squared for fixed effects are useful additions. Lastly, an approach using standardized generalized variance (SGV) can be used for covariance model selection. Package installation instructions can be found in the readme file.
| Version: | 0.1.2 |
| Imports: | mgcv, lmerTest, Matrix, pbkrtest, ggplot2, afex, stats, MASS, gridExtra, grid, data.table, dplyr |
| Suggests: | lme4, nlme, testthat |
| Published: | 2017-08-05 |
| DOI: | 10.32614/CRAN.package.r2glmm |
| Author: | Byron Jaeger [aut, cre] |
| Maintainer: | Byron Jaeger <byron.jaeger at gmail.com> |
| BugReports: | https://github.com/bcjaeger/r2glmm/issues |
| License: | GPL-2 |
| URL: | https://github.com/bcjaeger/r2glmm |
| NeedsCompilation: | no |
| Materials: | README |
| In views: | MixedModels |
| CRAN checks: | r2glmm results |
| Reference manual: | r2glmm.pdf |
| Package source: | r2glmm_0.1.2.tar.gz |
| Windows binaries: | r-devel: r2glmm_0.1.2.zip, r-release: r2glmm_0.1.2.zip, r-oldrel: r2glmm_0.1.2.zip |
| macOS binaries: | r-release (arm64): r2glmm_0.1.2.tgz, r-oldrel (arm64): r2glmm_0.1.2.tgz, r-release (x86_64): r2glmm_0.1.2.tgz, r-oldrel (x86_64): r2glmm_0.1.2.tgz |
| Old sources: | r2glmm archive |
| Reverse suggests: | variancePartition |
Please use the canonical form https://CRAN.R-project.org/package=r2glmm to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.