lme4 heteroscedasticity???
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