glmm.hp is an R package designed to evaluate the relative importance of collinear predictors within generalized linear mixed models (GLMMs). Since its initial release in January 2022, it has been rapidly gained recognition and popularity among ecologists. However, the previous
glmm.hp package was limited to work GLMMs derived exclusively from the
lme4 and
nlme packages. The latest
glmm.hp package has extended its functions. It has integrated results obtained from the
glmmTMB package, thus enabling it to handle zero-inflated generalized linear mixed models (ZIGLMMs) effectively. Furthermore, it has introduced the new functionalities of commonality analysis and hierarchical partitioning for multiple linear regression models by considering both unadjusted
R2 and adjusted
R2
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