glmm.hp: Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models (original) (raw)
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<doi:10.1093/jpe/rtac096>.
| Version: | 1.0-0 |
|---|---|
| Depends: | R (≥ 3.4.0), MuMIn, ggplot2, vegan |
| Imports: | lme4 |
| Published: | 2025-10-08 |
| DOI: | 10.32614/CRAN.package.glmm.hp |
| Author: | Jiangshan Lai  [aut, cre], Kim Nimon [aut], Yao Liu [aut] |
| Maintainer: | Jiangshan Lai |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | https://github.com/laijiangshan/glmm.hp |
| NeedsCompilation: | no |
| Citation: | glmm.hp citation info |
| CRAN checks: | glmm.hp results |
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