[R-sig-ME] lme4 heteroscedasticity???

[Paul Johnson]

You can model both heteroscedasticity and crossed random effects in nlme. Crossed random effects can be handled in nlme using pdBlocked and pdIdent. See p163-6 of Pinheiro, J.C. & Bates, D.M. (2000). Mixed-Effects Models in S and S-PLUS. Springer, New York.
Paul

On 13 Oct 2014, at 16:12, Douglas Bates <bates at stat.wisc.edu> wrote:

> 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, Košmelj, 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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