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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BlackWell Publishing Ltd
2014
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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 |
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). |
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