[R] Modelling Heteroscedastic Multilevel Models
Doran, Harold
HDoran at air.org
Tue Apr 17 14:13:11 CEST 2007
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: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Rense
> Nieuwenhuis
> Sent: Monday, April 16, 2007 4:37 PM
> To: r-help at 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]]
>
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