May I suggest the Exam data from the mlmRev package as an example. If you wish to have a random effect for Sex by school you could write the model as
lmer(test.result ~ homework + Sex + (Sex|school)) which gives correlated random effects for the overall achievement in schools and the differential effect of Sex by school. Alternatively you could write lmer(test.result ~ homework + Sex + (1|school) + (1|Sex:school)) which gives uncorrelated effects for the intercept by school and for the effect of sex by school. On 4/17/07, Doran, Harold <[EMAIL PROTECTED]> wrote: > I think there are many who can help, but this question is quite vague. > This assumes we have access to the book you note and can make sense of > your question w/o sample data. > > If you cannot find a sample data set please create a sample data file. > However, there are so many sample data sets in the mlmRev package and in > other places I doubt you will need to do this. For example, see the > egsingle or star data files that are education specific. But, if you for > some reason cannot do either at least give a good substantive > description of your data and the problem you are trying to solve. > > In the code you have below, you have a random intercept for each school, > but you remove the intercept in the fixed portion of the call. Also, > does it make sense to model Sex as random? This is a repeatable factor > (I hope), how can it be treated as a random draw from a population? > > > -----Original Message----- > > From: [EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] On Behalf Of Rense > > Nieuwenhuis > > Sent: Monday, April 16, 2007 4:37 PM > > To: r-help@stat.math.ethz.ch > > Subject: [R] Modelling Heteroscedastic Multilevel Models > > > > Dear ListeRs, > > > > I am trying to fit a heteroscedastic multilevel model using > > lmer{lme4- package). Take, for instance, the (fictive) model below. > > > > lmer(test.result ~ homework + Sex -1 + (1 | School)) > > > > Suppose that I suspect the error terms in the predicted > > values to differ between men and women (so, on the first > > level). In order to model this, I want the 'Sex'-variable to > > be random on the first level, as described in Snijders & > > Bosker, page 110. > > > > Does anybody know if this is possible and how this can be > > done using R? > > > > Many thanks in advance. > > > > Rense Nieuwenhuis > > > > > > PS. Please excuse me for not providing a self-contained > > example. I couldn't find a data-set in the lme4-package that > > fitted my question. > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@stat.math.ethz.ch mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.