[R-sig-ME] differing variances within different random effects levels
david.r.afshartous at Vanderbilt.Edu
Tue Feb 15 14:53:52 CET 2011
Thanks Reinhold. I had forgotten about that one also. Actually, I
just found the part of the thread the has the summary I was thinking about:
On 02/15/2011 12:27 AM, Reinhold Kliegl wrote:
> 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:
>> There are a few old threads that you might find useful, search the
>> 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.
>> 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
>>> (or fixed=response~treatment, random=~treatment|species/indiv in lme)
>>> which would give me random effects
>>> (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 ...
>>> Ben Bolker
>>> R-sig-mixed-models at r-project.org mailing list
>> David Afshartous, Ph.D.
>> Research Associate Professor
>> School of Medicine
>> Department of Biostatistics
>> Vanderbilt University
>> [[alternative HTML version deleted]]
>> R-sig-mixed-models at r-project.org mailing list
David Afshartous, Ph.D.
Research Associate Professor
School of Medicine
Department of Biostatistics
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