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Extension of Nakagawa & Schielzeth's R(2)(GLMM) to random slopes models

1. Nakagawa & Schielzeth extended the widely used goodness-of-fit statistic R(2) to apply to generalized linear mixed models (GLMMs). 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 an...

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Detalles Bibliográficos
Autor principal: Johnson, Paul CD
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4368045/
https://www.ncbi.nlm.nih.gov/pubmed/25810896
http://dx.doi.org/10.1111/2041-210X.12225
Descripción
Sumario:1. Nakagawa & Schielzeth extended the widely used goodness-of-fit statistic R(2) to apply to generalized linear mixed models (GLMMs). 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. 2. 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).