R2 for Negative Binomial calculated with GLMMADMB
Dear Jens Our proposed R2 is not 'the' R2 but is also an R2 for mixed models that has several of the useful properties of traditional R2 - actually first proposed by Snijders & Bosker (1994). Let?s say NB(lambda, theta) with the log link ? the mean = lambda, and the variance = lambda+ lambda^2/theta The level 1 variance (on the link scale) should be ln(1+1/lambda+1/theta): see the Appendix of our paper, Nakagawa & Schielzeth (2013) For lambda, it is good to use mean(Y) (Y is the response; counts) and the package should give you the value of theta (also, one should use mean(Y) for Possion models). Here the level 1 variance, sigma^2_1= sigma^2_e (additive over-dispersion)+sigma^2_d (distribution specific) = sigma^2_epsilon (residual variance) as in our paper (2013). But Holger and I are doing some simulation study to check this first before its use, and we think we can extend the proposed R2 to other distributions although we need to test a few things first (we should be ready in one month or so). Best wishes, Shinichi Shinichi Nakagawa, PhD (Associate Professor of Behavioural Ecology) Department of Zoology University of Otago 340 Great King Street P. O. Box 56 Dunedin, New Zealand Tel: +64-3-479-5046 Fax: +64-3-479-7584 http://sparrow.otago.ac.nz/
From: R-sig-mixed-models [r-sig-mixed-models-bounces at r-project.org] on behalf of Jens Oldeland [fbda005 at uni-hamburg.de]
Sent: Thursday, December 18, 2014 4:18 AM
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB
Sent: Thursday, December 18, 2014 4:18 AM
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] R2 for Negative Binomial calculated with GLMMADMB
Dear List-members, recently, the R2 calculations for GLMMs invented by Schielzieth and Nakagawa 2012 [1] were implemented into the MuMIn package. This is incredibly good news, as many colleagues still require R2 to understand a model output. I invested 2 weeks in lengthy calculations of about 20 negative binomial GLMMs using the glmmADMB package. Now, my colleagues want the R2 (me too), however, sadly, the MuMIn functions do only work for binomial and poisson GLMMS. Further, it seems that the functions do not recognize the glmmADMB package but prefer (g)lmer output. Now my question: Does anybody of you know if this is "easy" to implement and if so "how"? I tried to redo the code provided here (actually posing the same question) but failed...: http://stats.stackexchange.com/questions/109215/r%C2%B2-squared-from-a-generalized-linear-mixed-effects-models-glmm-using-a-negat Or does anybody know if in the near future (this year?) it will be implemented somewhere? Is it possible to transform a GLMMADMB object into an lmer object? Any hints are most welcome, merry Xmas Jens [1] Nakagawa, S., & Schielzeth, H. (2013). A general and simple method for obtaining R2 from generalized linear mixed-effects models./Methods in Ecology and Evolution/,/4/(2), 133-142. -- +++++++++++++++++++++++++++++++++++++++++ Dr. Jens Oldeland Post-Doc Researcher & Lecturer @ BEE Managing Editor - Biodiversity & Ecology Biodiversity, Ecology and Evolution of Plants (BEE) Biocentre Klein Flottbek and Botanical Garden University of Hamburg Ohnhorststr. 18 22609 Hamburg, Germany Tel: 0049-(0)40-42816-407 Fax: 0049-(0)40-42816-543 Mail: jens.oldeland at uni-hamburg.de Oldeland at gmx.de Skype: jens.oldeland http://www.biologie.uni-hamburg.de/bzf/fbda005/fbda005.htm http://www.biodiversity-plants.de/biodivers_ecol/biodivers_ecol.php +++++++++++++++++++++++++++++++++++++++++ [[alternative HTML version deleted]] _______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models