Message-ID: <CAO7JsnSbzP++fHY5ji+5KY26sY_U+WL-fSxq5EvsD6dd8D1GKg@mail.gmail.com>
Date: 2014-10-13T15:12:44Z
From: Douglas Bates
Subject: lme4 heteroscedasticity???
In-Reply-To: <4152C532A3804441A1228603786ADAE606B22489@MAIL-BF>
It is best to send questions like this to the
R-SIG-Mixed-Models at R-Project.org mailing list, which I am cc:ing on this
reply. Several of those who read that list can respond more quickly than I
am able to.
As far as I know there is not yet the capability in lme4 to model
heteroscedasticity in the distribution of the response given the random
effects.
On Mon, Oct 13, 2014 at 6:01 AM, Ko?melj, Katarina <
Katarina.Kosmelj at bf.uni-lj.si> wrote:
> Hello,
>
> I am analyzing a mixed model with three crossed factors, two random
> (sample, laboratory) and one fixed (method); the response variable is the
> number of somatic cells in milk. The main question is: is the precision of
> the means of the three method is comparable? Therefore, I would like to
> compare a model with different variances for the methods with the model
> considering the same variance for the methods.
>
>
>
> In nlme, this is feasible, however, two crossed random factors can not be
> tackled, this can be analyzed with lme4.
>
>
>
> In nlme, the problem of heteroscedasticity if solved. Is this problem
> solved in lme4 yet?
>
> Do you have any suggestion how to deal with this problem?
>
>
>
> Regards,
>
> Katarina
>
>
>
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