Extract a variance estimate per level of random effect
Hi If you are using lme() you can use the VarCorr() function to get the between and with-in variance for the random part of the model. For a good explanation you can try http://plantecology.syr.edu/fridley/bio793/mixed1.html Beatriz de Francisco Mora PhD Student The Scottish Association for Marine Science Scottish Marine Institute Oban PA37 1QA Tel: 06131 559000 (switchboard) Fax: 01631559001 E. beatriz.defrancisco at sams.ac.uk http://www.smi.ac.uk/beatriz-de-francisco Message: 1 Date: Mon, 18 Jun 2012 12:43:12 +0200 From: Luca Borger <lborger at cebc.cnrs.fr> To: Alan Haynes <aghaynes at gmail.com> Cc: r-sig-mixed-models at r-project.org Subject: Re: [R-sig-ME] Extract a variance estimate per level of random effect Message-ID: <4FDF0640.7010908 at cebc.cnrs.fr> Content-Type: text/plain; charset=ISO-8859-1; format=flowed >Perhaps theres a way to get at the estimates it produces... summary(myModel)$modelStruc$varStruc Le 18/06/2012 11:39, Alan Haynes a ?crit :
Hi there, If youre not fixed on either lmer or mcmcglmm particularly, ot might be possible using lme... Using the weights argument you can allow an individuals variance (in your case) to vary. Perhaps theres a way to get at the estimates it produces... HTH Alan -------------------------------------------------- Email: aghaynes at gmail.com Mobile: +41794385586 Skype: aghaynes On 18 June 2012 11:06, Luca Borger <lborger at cebc.cnrs.fr> wrote:
Hello, I think there have been some recent papers on estimating individual variability in behaviour, but in any case is this useful?: library(lme4) fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy) str(ranef(fm1, postVar = TRUE)) attr((ranef(fm1, postVar = TRUE))[[1]],"postVar") HTH Luca # Forthcoming book chapter # Dispersal Ecology and Evolution (ch. 17) # http://ukcatalogue.oup.com/**product/9780199608904.do<http://ukcatalogue.oup.com/product/9780199608904.do> ------------------------------**------------------------------**--------- Luca Borger Postdoctoral Research Fellow Centre d'Etudes Biologiques de Chiz? CNRS (UPR1934); INRA (USC1339) 79360 Villiers-en-Bois, France Tel: +33 (0)549 09 96 13 Fax: +33 (0)549 09 65 26 email: lborger at cebc.cnrs.fr Web: http://cnrs.academia.edu/**LucaBorger<http://cnrs.academia.edu/LucaBorger> Researcher ID: http://www.researcherid.com/**rid/C-6003-2008<http://www.researcherid.com/rid/C-6003-2008> Google Scholar: http://scholar.google.com/**citations?user=D5CTvNUAAAAJ<http://scholar.google.com/citations?user=D5CTvNUAAAAJ> ------------------------------**------------------------------**--------- # Newly published! Animal Migration: A synthesis (ch. 8): # http://ukcatalogue.oup.com/**product/9780199568994.do<http://ukcatalogue.oup.com/product/9780199568994.do> Le 18/06/2012 10:29, Samantha Patrick a ?crit : Hi
I am currently trying to estimate how consistent individuals are in a trait. I want to produce an estimate of the variability for each level of a random effect (ID). I can do this simply by calculation the variance for each ID separately but I am trying to extract this information from a mixed model (either in lmer or mcmcglmm). I have trawled the mailing list but can not find any answers. As an simplified dummy example I have 2 individuals, each with 5 observations of a trait. I can calculate 2 variances, using the 5 observations for each individual. head(Data) ID trait1 1 10 1 15 1 12 1 19 1 11 2 9 2 10 2 9 2 10 2 10 Variance for 1 = 4.67 Variance for 2 = 0.3 Alternatively I can fit a model of: model1<-lmer(trait1 ~(1|ID)) From the variance covariance matrix I can easily extract the between and within group variances, but is there a way to extract individual variance estimates? Many Thanks Sam
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