R-Squared Measures for Multilevel Models

Generates both total- and level-specific R-squared measures from Rights and Sterba’s (2019) 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) ).


Reference manual

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0.3.1 by Mairead Shaw, a month ago


Report a bug at https://github.com/mkshaw/r2mlm/issues

Browse source code at https://github.com/cran/r2mlm

Authors: Mairead Shaw [aut, cre] , Jason Rights [aut] , Sonya Sterba [aut] , Jessica Flake [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports broomExtra, dplyr, magrittr, rlang, rockchalk, stringr, tidyselect

Depends on lme4, nlme

Suggests testthat, Matrix

See at CRAN