Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models

Conducts hierarchical partitioning to calculate individual contributions of each predictor (fixed effects) towards marginal R2 for generalized linear mixed-effect model (including lm, glm and glmm) based on output of r.squaredGLMM() in 'MuMIn', applying the algorithm of Lai J.,Zou Y., Zhang S.,Zhang X.,Mao L.(2022)glmm.hp: an R package for computing individual effect of predictors in generalized linear mixed models.Journal of Plant Ecology,15(6)1302-1307.


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install.packages("glmm.hp")

1.0-0 by Jiangshan Lai, a year ago


https://github.com/laijiangshan/glmm.hp


Browse source code at https://github.com/cran/glmm.hp


Authors: Jiangshan Lai [aut, cre] (ORCID: , Kim Nimon [aut] , Yao Liu [aut]


Documentation:   PDF Manual  


GPL license


Imports lme4

Depends on MuMIn, ggplot2, vegan


Imported by upset.hp.


See at CRAN