[R-sig-ME] differing variances within different random effects levels

[Reinhold Kliegl]

I think it was this very useful thread David refers to
:
Subject:	[R-sig-ME] getVarCov for lmer()	
From:	Douglas Bates (bat... at stat.wisc.edu)
Date:	Feb 2, 2008 3:47:12 pm
List:	org.r-project.r-sig-mixed-models

Reinhold Kliegl

On Mon, Feb 14, 2011 at 10:47 PM, David Afshartous
<david.r.afshartous at vanderbilt.edu> wrote:
> Ben,
> There are a few old threads that you might find useful, search the
> following:
>
> random effect variance per treatment group in lmer
> heteroscedastic model in lme4
> Stratifying level-1 variance with lmer()
> Different random effects variances for outcomes and groups
> Behavior of coef() for lmer() model w/ level-2 variance stratified
>
> I think in one of them I provided a summary of some of the issues but I
> can't seem to find it at the moment.
>
> Cheers,
> David
>
>
>
>
>
> On 02/14/2011 02:53 PM, Ben Bolker wrote:
>>    This is a question that's been bothering me for a while.  The answer
>> might be "read sections 4.2.2 and 4.2.3 of Pinheiro and Bates 2000
>> again, more carefully", but if anyone has done this before I wouldn't
>> mind some hints ...
>>
>>    Consider a simplified version of the previous poster's example.
>> Suppose I have a randomized block design where T treatments are done for
>> each of N individuals within each of S species. My basic model for this
>> would be
>>
>>    response~treatment+(treatment|species/indiv)
>>
>> (or fixed=response~treatment, random=~treatment|species/indiv in lme)
>>
>> which would give me random effects
>>
>> 1|species
>> 1|indiv:species
>> treatment|species
>> treatment|indiv:species
>>
>> (and correlations between intercept and treatment effects at species and
>> indiv:species level).
>>
>>    Suppose now that I think the *variance* among individuals varies among
>> species.  As far as I can tell, lme/lmer assume that this variance is
>> constant across species.  If I wanted variance across *observations*
>> (i.e. residual variance) to vary across species I could do it via
>> something like weights=varIdent(~species), but this only works for
>> residual variance.
>>
>>    I suspect I could work out some way to do this with MCMCglmm, and I
>> don't have an immediate need for it, but I thought I would ask ...
>>
>>   thanks
>>      Ben Bolker
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
> --
> David Afshartous, Ph.D.
> Research Associate Professor
> School of Medicine
> Department of Biostatistics
> Vanderbilt University
>
>
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