[R-sig-ME] var estimates of the random effects variance in lme4

[Yuan Yuan]

Hi, Colin
Thank you for the reply.
What I want is to simulate  sd of random effects from their estimated 
asymptotic distribution in bootstrapping.
I will have a look at the link.

Joyce
Colin Millar wrote:
> Hi Joyce,
>  
> If you want to simulate from the model parameters, including 
> simulating from the variance component distribution you can get pretty 
> exact distributions (all beit Bayesian ...) using Havad Rue's INLA 
> package which can be found in http://www.r-inla.org/.  You had to use 
> your wits to simulate from the posterior distributions last time i 
> looked (abt 4 months ago), but he is always working on it so it may be 
> more user freindly now. 
>  
> Its strength is structured random effects, however it will also do iid 
> random effects so is a Bayesian alternative in R to lme4.  Its 
> definately worth a reccy.
>  
> Hope this helps,
> Colin
>
> ------------------------------------------------------------------------
> *From:* r-sig-mixed-models-bounces at r-project.org on behalf of Douglas 
> Bates
> *Sent:* Wed 03/03/2010 18:21
> *To:* Yuan Yuan
> *Cc:* r-sig-mixed-models at r-project.org
> *Subject:* Re: [R-sig-ME] var estimates of the random effects variance 
> in lme4
>
> On Wed, Mar 3, 2010 at 11:57 AM, Yuan Yuan <joyce at mcs.st-and.ac.uk> wrote:
> > Hi, all
> > For an estimate of the parameter, we have a variance estimate 
> associated with
> > the parameter estimate.
>
> Usually called the standard error of a parameter estimate.
>
> > Say, let beta denote the fixed effect in linear regresssion, we have 
> an estimate
> > given the data,\hat{beta} and its variance estimate 
> \hat{var}[\hat{beta}].
> > My question is, for the random effects, denoted by b, sd(b) is our 
> parameter of
> > interest, but I can not find the estimated sd[sd(b)]. There is 
> \hat{sd(b)} in
> > the summary list, but not \hat{sd}{\hat{sd(b)}}.
>
> > I was told that you can find estimted var[var(random effect)] in SAS
> > Is there anyone can tell me whether or not I can find var[var(random 
> effect)] in
> > the output given by glmer in package lme4?
>
> It is true that SAS does provide a standard error of a variance
> estimate from SAS PROC MIXED.  If you check the book by West, Welch
> and Galecki (ISBN 1-58488-480-0) you will see that all of the software
> systems they use to fit mixed-effects models provide such standard
> errors, except for the nlme package in R and the lme4 package for R.
> This is intentional.  Standard errors of variance estimates are
> nonsensical because the estimators are highly skewed.  This is
> discussed and illustrated in chapters 1 and 2 of the book I am writing
> for which the chapter drafts are available at
> http://lme4.R-forge.R-project.org/book/ 
> <http://lme4.r-forge.r-project.org/book/>
>
> > Thank you very much.
> >
> > Cheers,
> > Joyce
> > --
> > Yuan(Joyce) Yuan
> > PhD student in Statistics
> >
> > CREEM - Centre for Research into Ecological and Environmental Modelling
> > University of St Andrews
> > The Observatory
> > Buchanan Gardens
> > St Andrews
> > Fife
> > KY16 9LZ
> > Scotland
> >
> > Tel: +44 (0)1334 461826
> > Fax: +44 (0)1334 461800
> >
> >
> > ------------------------------------------------------------------
> > University of St Andrews Webmail: https://webmail.st-andrews.ac.uk 
> <https://webmail.st-andrews.ac.uk/>
> >
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> >
>
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-- 
Yuan(Joyce) Yuan
PhD student 

CREEM - Centre for Research into Ecological and Environmental Modelling
University of St Andrews
The Observatory
Buchanan Gardens
St Andrews
Fife
KY16 9LZ
Scotland

Tel: +44 (0)1334 461826
Fax: +44 (0)1334 461800

The University of St Andrews is a charity registered in Scotland: No SC013532