Spencer Graves <[EMAIL PROTECTED]> writes:
> Have you considered "lme"? For applications like this, I highly
> recommend Pinheiro and Bates (2000) Mixed-Effects Models in S and
> S-Plus (Springer). I failed to produce anything with "lme" until I
> read this book. hope this helps. spencer graves
Actually lme is better suited to nested designs than to crossed
designs and lme doesn't handle generalized linear mixed models.
GLMM from package lme4 does handle generalized linear mixed models but
does not handle crossed random effects easily.
I'm working on code that will handle nested, crossed and partially
crossed random effects but it will be some time before it appears in a
finished package
>
>
> David Firth wrote:
>
> > Are there facilities in R or packages to estimate the parameters of
> > a (generalized) linear mixed model like this one: the design is
> > crossed, and response $y_{ij}$ relates to fixed and random effects
> > through a linear predictor
>
> > \[
> > \eta_{ij} = \beta x_{ij} + U_i - U_j
> > \]
> > where $U_1, U_2, \ldots$ are iid $N(0, \tau^2)$.
> >
> > Any suggestions would be welcomed.
> >
> > David
> >
> > Professor David Firth
> > Dept of Statistics
> > University of Warwick
> > Coventry CV4 7AL
> > United Kingdom
> >
> > Voice: +44 (0)247 657 2581
> > Fax: +44 (0)247 652 4532
> > Web: http://www.warwick.ac.uk/go/dfirth
> >
> > ______________________________________________
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> > PLEASE do read the posting guide!
> > http://www.R-project.org/posting-guide.html
>
>
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--
Douglas Bates [EMAIL PROTECTED]
Statistics Department 608/262-2598
University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/
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