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>).

Getting started

Package details

AuthorMairead Shaw [aut, cre], Jason Rights [aut], Sonya Sterba [aut], Jessica Flake [aut]
MaintainerMairead Shaw <mairead.shaw@mail.mcgill.ca>
LicenseGPL-3
Version0.3.0
URL https://github.com/mkshaw/r2mlm
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("r2mlm")

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r2mlm documentation built on June 5, 2021, 1:05 a.m.