[R-sig-ME] Standard errors for random effects

[Doran, Harold]

I don't think this is what the OP is referring to. If you want the standard errors of the conditional means, then you can extract them as follows:

(fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
attr( ranef(fm1, postVar = TRUE)[[1]], "postVar")

This is the variance/covariance matrix of the conditional means. So, grab what you need from the array here. The postVar argument is used to get the so called posterior means. However, I ssuepcta t some point this term will be deprecated and replaced with something more appropriate. 

-----Original Message-----
From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of Luca Borger
Sent: Thursday, April 01, 2010 10:55 AM
To: Tahira Jamil; r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Standard errors for random effects

Hello,

no, as the sampling distribution of random effects/variance estimates is 
usually strongly asymmetric and thus better alternatives should be used. See 
the mail archives for posts by Douglas Bates or the drafts of his 
forthcoming book or the wiki for mixed models:

http://glmm.wikidot.com/faq
Standard errors of variance estimates
  a.. Paraphrasing Doug Bates: the sampling distribution of variance 
estimates is in general strongly asymmetric: the standard error may be a 
poor characterization of the uncertainty.
  b.. Alternatives?
    a.. The development version of lme4, lme4a, allows for computing 
likelihood profiles of variances.
    b.. An MCMC-based approach (MCMCglmm, etc.) will provide posterior 
distributions of the variance parameters: quantiles or credible intervals 
(HPDinterval() in coda()) will characterize the uncertainty.



HTH,

Cheers,

Luca


----- Original Message ----- 
From: "Tahira Jamil" <tahirajamil at yahoo.com>
To: <r-sig-mixed-models at r-project.org>
Sent: Thursday, April 01, 2010 10:41 AM
Subject: [R-sig-ME] Standard errors for random effects


> Hi
> I am wondering how can we extract standard errors of random effects. Is it 
> possible or not in lme4.
> Best regards
>
> Tahira Jamil
> PhD student
> Biometris Wageningen
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>

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