[R-sig-ME] Confidence intervals for effects in glmer()

[Ben Bolker]

  It depends on what approximations you're willing to accept.

  Crudely doing +/- 2 standard deviations, or (DANGER DANGER)
using the 'known' df to compute t-scores (the "gm1" example
given in ?glmer has a fairly straightforward structure, with
15 groups):

library(lme4)
example(glmer)
s <- summary(gm1)@coefs

fac <- 2
s[,"Estimate"]+fac*outer(c(-1,1),s[,"Std. Error"])

fac <- qt(0.975,df=14)
s[,"Estimate"]+fac*outer(c(-1,1),s[,"Std. Error"])


  Does anyone know the current status of mcmcsamp,
either for LMMs or for GLMMs ... ?

  Ben Bolker

Robert A. LaBudde wrote:
> This may be blindingly obvious to the casual observer, but I'm 
> chagrined to admit I'm stumped.
> 
> I'm fitting a simple mixed effect logistic model using 'lme4':
> 
> require('lme4')
> fit4<- glmer(x ~ 1 + 1|lab, data=eg, nAGQ=5, family='binomial')
> summary(fit4)
> ranef(fit4)
> 
> I would like 95% confidence intervals on 'lab' and the residuals effects.
> 
> Using lme() in 'nlme', I had the function intervals() available. Now I don't.
> 
> Any hints to de-perplex a novice?
> 
> Thanks.
> ================================================================
> Robert A. LaBudde, PhD, PAS, Dpl. ACAFS  e-mail: ral at lcfltd.com
> Least Cost Formulations, Ltd.            URL: http://lcfltd.com/
> 824 Timberlake Drive                     Tel: 757-467-0954
> Virginia Beach, VA 23464-3239            Fax: 757-467-2947
> 
> "Vere scire est per causas scire"
> 
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-- 
Ben Bolker
Associate professor, Biology Dep't, Univ. of Florida
bolker at ufl.edu / www.zoology.ufl.edu/bolker
GPG key: www.zoology.ufl.edu/bolker/benbolker-publickey.asc