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Extension of Nakagawa & Schielzeth's R2GLMM to random slopes models

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Johnson, Paul C.D.·2014·Methods in Ecology and Evolution

Abstract

Summary: Nakagawa & Schielzeth extended the widely used goodness‐of‐fit statistic R2 to apply to generalized linear mixed models (GLMM s). However, their R2GLMM 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 R2GLMM 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 R2GLMM.

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Research works printed but not linked: 7

  1. 10.1093/biomet/57.1.215 · doi:10.1093/biomet/57.1.215
  2. 10.1016/j.tree.2008.10.008 · DOI · Paper page
  3. 10.1017/CBO9780511810176 · DOI · Paper page
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  5. R Core Team, 2014, R: A Language and Environment for Statistical Computing
  6. 10.1177/0049124194022003004 · DOI · Paper page
  7. Snijders T.A.B., 2012, Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling

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Metadata

Authors
Johnson, P. C. D.
Venue
Methods in Ecology and Evolution
Publisher
Wiley
Published
2014-07-23
Volume
5
Issue
9
Pages
944-946
ISSN
2041-210X (ISSN-L)
OpenAlex
W2060444352
Cited by
948
References
3
FWCI
91.42
Type
journal article
Language
en
Open access
hybrid
Funders
Biotechnology and Biological Sciences Research Council (BB/K004484/1)

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CoChat. (2026). Citation check: Extension of Nakagawa & Schielzeth's R2GLMM to random slopes models. https://app.cochat.ai/papers/10.1111/2041-210x.12225
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Johnson, P. C. D. (2014). Extension of Nakagawa & Schielzeth's R2GLMM to random slopes models. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210x.12225

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