Partitioning R2 in GLMMs

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) and Nakagawa, Johnson & Schielzeth (2017) .


Reference manual

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0.9.1 by Martin A. Stoffel, a year ago

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Authors: Martin A. Stoffel [aut, cre] , Shinichi Nakagawa [aut] , Holger Schielzeth [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports methods, stats, lme4, pbapply, dplyr, purrr, rlang, tibble, magrittr, ggplot2, tidyr

Suggests testthat, future, furrr, knitr, rmarkdown, patchwork, covr

See at CRAN