[R-sig-ME] heteroscedastic model in lme4

[Dimitris Rizopoulos]

I think not, because Anna wanted to model the variance of the within 
measurement error terms not the variance of the random effects.

As far as I know, the design philosophy of lme4 is to allow for flexible 
specifications of the random effects part of the mixed model that is 
assumed to account for the main part of variability in the data.

Best,
Dimitris


Alan Cobo-Lewis wrote:
> Anna,
> 
> lme4 cannot handle certain kinds of heteroscedasticity, but I believe it can handle the kind you have in mind. Search the r-sig-mixed-models archive for a discussion involving me and David Afshartous, especially the summary message titled
> "[R-sig-ME] random effect variance per treatment group in lmer" that David posted 07/13/2007 04:18:08 PM
> 
> I can't be certain that the suggestion below would work without knowing more about your design, but if width were a factor with three levels then you might try setting up indicator variables Wind1, Wind2, and Wind3 (that each take on the value 1
> when a site is at the indicator's target width and 0 otherwise) and then fit the model with something like
> mrem <- lmer( log(Nhat+1)~Group + GreenPerc + sess + crop + VegDensity + Group:sess + Group:VegDensity + (0+Wind1|site) + (0+Wind2|site) + (0+Wind3|site), data=all, method="REML" )
> 
> alan
> 
> 
> r-sig-mixed-models at r-project.org on Friday, December 19, 2008 at 6:00 AM -0500 wrote:
>> Message: 1
>> Date: Thu, 18 Dec 2008 11:23:46 +0000
>> From: "Renwick, A. R." <a.renwick at abdn.ac.uk>
>> Subject: [R-sig-ME] heteroscedastic model in lme4
>> To: "'r-sig-mixed-models at r-project.org'"
>> 	<r-sig-mixed-models at r-project.org>
>> Message-ID:
>> 	<B9D1301370916C44B5874AF340C18B9B28AE890D50 at VMAILB.uoa.abdn.ac.uk>
>> Content-Type: text/plain; charset="us-ascii"
>>
>> I have been using the nlme package to run some LMM's, however I would like to try rerunning them using the lme4 package so that I can use mcmc sampling.  The data I am using shows some heteroscesdasticity of the within error group and so I have
>> been using the 'weights' argument and the varIdent variance function structure to allow different variances for each level of my factor (patch width).
>>
>> My problem is how to code for a heteroscedastic model in lme4 and any suggestion wouuld be much apprecaited.
>>
>> The code I used in the nlme package:
>>
>> # model fit using "REML"
>> mrem<-lme(log(Nhat+1)~Group + GreenPerc + sess + crop + VegDensity + Group:sess + Group:VegDensity ,random=~1|Site, data=all,
>>       method="REML",correlation=NULL,weights=varIdent(form=~1|width))
>>
>>
>> Many thanks,
>> Anna
>>
>> Anna Renwick
>> Institute of Biological & Environment Sciences
>> University of Aberdeen
>> Zoology Building
>> Tillydrone Avenue
>> Aberdeen
>> AB24 2TZ
>>
>>
>> The University of Aberdeen is a charity registered in Scotland, No SC013683.
> 
> 
> --
> Alan B. Cobo-Lewis, Ph.D.		(207) 581-3840 tel
> Department of Psychology		(207) 581-6128 fax
> University of Maine
> Orono, ME 04469-5742     		alanc at maine.edu
> 
> http://www.umaine.edu/visualperception
> 
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-- 
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus Medical Center

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