r2mlm: R-Squared Measures for Multilevel Models

Generates both total- and level-specific R-squared measures from Rights and Sterba’s (2019) <doi:10.1037/met0000184> framework of R-squared measures for multilevel models with random intercepts and/or slopes, which is based on a complete decomposition of variance. Additionally generates graphical representations of these R-squared measures to allow visualizing and interpreting all measures in the framework together as an integrated set. This framework subsumes 10 previously-developed R-squared measures for multilevel models as special cases of 5 measures from the framework, and it also includes several newly-developed measures. Measures in the framework can be used to compute R-squared differences when comparing multilevel models (following procedures in Rights & Sterba (2020) <doi:10.1080/00273171.2019.1660605>). Bootstrapped confidence intervals can also be calculated. To use the confidence interval functionality, download bootmlm from <https://github.com/marklhc/bootmlm>.

Version: 0.3.7
Depends: lme4 (≥ 1.1.23), nlme (≥ 3.1.14), R (≥ 3.2.0)
Imports: dplyr (≥ 0.8.5), magrittr (≥ 1.5), methods (≥ 3.6.3), rlang (≥ 0.4.6), rockchalk (≥ 1.8.157), stringr (≥ 1.4.0), tidyselect (≥ 1.0.0)
Suggests: bootmlm, testthat, Matrix
Published: 2023-12-20
DOI: 10.32614/CRAN.package.r2mlm
Author: Mairead Shaw [aut, cre], Jason Rights [aut], Sonya Sterba [aut], Jessica Flake [aut]
Maintainer: Mairead Shaw <mairead.shaw at mail.mcgill.ca>
BugReports: https://github.com/mkshaw/r2mlm/issues
License: GPL-3
URL: https://github.com/mkshaw/r2mlm
NeedsCompilation: no
Citation: r2mlm citation info
Materials: README NEWS
CRAN checks: r2mlm results


Reference manual: r2mlm.pdf


Package source: r2mlm_0.3.7.tar.gz
Windows binaries: r-devel: r2mlm_0.3.7.zip, r-release: r2mlm_0.3.7.zip, r-oldrel: r2mlm_0.3.7.zip
macOS binaries: r-release (arm64): r2mlm_0.3.7.tgz, r-oldrel (arm64): r2mlm_0.3.7.tgz, r-release (x86_64): r2mlm_0.3.7.tgz, r-oldrel (x86_64): r2mlm_0.3.7.tgz
Old sources: r2mlm archive


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