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Extension of Nakagawa & Schielzeth's R 2 GLMM to random slopes models
Author(s) -
Johnson Paul C.D.
Publication year - 2014
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12225
Subject(s) - generalized linear mixed model , random effects model , mixed model , mathematics , statistics , statistical physics , goodness of fit , extension (predicate logic) , computer science , physics , medicine , meta analysis , programming language
Summary Nakagawa & Schielzeth extended the widely used goodness‐of‐fit statistic R 2 to apply to generalized linear mixed models ( GLMM s). However, their R 2 GLMM method is restricted to models with the simplest random effects structure, known as random intercepts models. It is not applicable to another common random effects structure, random slopes models. I show that R 2 GLMM can be extended to random slopes models using a simple formula that is straightforward to implement in statistical software. This extension substantially widens the potential application of R 2 GLMM .