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Volumn 5, Issue 9, 2014, Pages 944-946

Extension of Nakagawa & Schielzeth’s R2 GLMM to random slopes models

Author keywords

Coefficient of determination; Generalized linear mixed model; Random regression; Random slopes model

Indexed keywords


EID: 85027343577     PISSN: None     EISSN: 2041210X     Source Type: Journal    
DOI: 10.1111/2041-210X.12225     Document Type: Article
Times cited : (779)

References (11)
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    • R package version 1.10.0
    • Bartoń, K. (2014) MuMIn: Multi-model inference. R package version 1.10.0. Retrieved May 14, 2014, from http://cran.r-project.org/package=MuMIn
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    • Bartoń, K.1
  • 2
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    • On a Mixture of Normal Distributions
    • Behboodian, J. (1970) On a Mixture of Normal Distributions. Biometrika, 57, 215–217.
    • (1970) Biometrika , vol.57 , pp. 215-217
    • Behboodian, J.1
  • 4
    • 0020333131 scopus 로고
    • Random-effects models for longitudinal data
    • Laird, N.M. & Ware, J.H. (1982) Random-effects models for longitudinal data. Biometrics, 38, 963–974.
    • (1982) Biometrics , vol.38 , pp. 963-974
    • Laird, N.M.1    Ware, J.H.2
  • 7
    • 84873554456 scopus 로고    scopus 로고
    • Ageneral and simplemethod for obtaining R^2 from generalized linear mixed-effects models
    • Nakagawa, S. & Schielzeth, H. (2013) Ageneral and simplemethod for obtaining R^2 from generalized linear mixed-effects models. Methods in Ecology and Evolution, 4, 133–142.
    • (2013) Methods in Ecology and Evolution , vol.4 , pp. 133-142
    • Nakagawa, S.1    Schielzeth, H.2
  • 8
    • 34247513357 scopus 로고    scopus 로고
    • The evolutionary ecology of individual phenotypic plasticity in wild populations
    • Nussey, D.H., Wilson, A.J. & Brommer, J.E. (2007) The evolutionary ecology of individual phenotypic plasticity in wild populations. Journal of Evolutionary Biology, 20, 831–844.
    • (2007) Journal of Evolutionary Biology , vol.20 , pp. 831-844
    • Nussey, D.H.1    Wilson, A.J.2    Brommer, J.E.3
  • 9
    • 84907095419 scopus 로고    scopus 로고
    • R: A Language and Environment for Statistical Computing
    • Vienna, Austria. Retrieved April 10
    • R Core Team (2014) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved April 10, 2014, from http://www.r-project.org/
    • (2014) R Foundation for Statistical Computing


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.