laijiangshan/glmm.hp: 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<doi:10.1093/jpe/rtac096>.

Getting started

Package details

MaintainerJiangshan Lai <lai@njfu.edu.cn>
LicenseGPL
Version0.1-7
URL https://github.com/laijiangshan/glmm.hp
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("laijiangshan/glmm.hp")
laijiangshan/glmm.hp documentation built on Dec. 15, 2024, 4:31 p.m.