Residual variance random effect GLMM
I'll second Thierry's comments, but also point out that there are some recipes for generalizing the idea of "variance explained": see papers by Nakagawa and Schielzeth or https://rawgit.com/bbolker/mixedmodels-misc/master/glmmFAQ.html#how-do-i-compute-a-coefficient-of-determination-r2-or-an-analogue-for-glmms I've now created a tinyURL link for the GLMM FAQ: http://tinyurl.com/glmmFAQ . Comments, pull requests, etc. welcome! cheers Ben Bolker
On 16-06-20 03:50 AM, Thierry Onkelinx wrote:
Dear Sara, Unlike a linear model, generalised linear models don't have a residual variance. A linear model assumes a Gaussian distribution with two parameters: mean and standard error which are independent. Generalised linear models use distributions how dependent on only one parameter (binomial, Poisson). Mean and variance of those distributions are defined by the same parameter. In case a generalised linear model uses a two parameter distribution (e.g. negative binomial), still the mean and variance are influenced by a common parameter (mean = mu, var = mu + mu ^ 2 /theta). Best regards, ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey 2016-06-18 17:30 GMT+02:00 Fraixedas, Sara <sara.fraixedas at helsinki.fi>:
Dear all,
I want to calculate the percentage variance explained by a random effect
in a GLMM fitted using the "glmmADMB" package. For that I would need to
know what is the residual variance but it is not given in
"VarCorr.glmmadmb" or in the summary output command.
How can I extract the residual variance from a random effect in this
particular case?
Thank you in advance,
Sara Fraixedas
Doctoral Student
The Helsinki Lab of Ornithology (HelLO) Finnish Museum of Natural
History P.O. Box 17
00014 University of Helsinki, Finland
Tel. +358-9-19128851
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