[R] mixed effect-models

[Grathwohl,Dominik,LAUSANNE,NRC/NT]

Do I understand right, there is no multinom (nnet), with random effects
available in R!
Do I need to switch to SAS, PROC NLMIXED applying Agresti's example:
http://stat2.uibk.ac.at/SMIJ/hartzel_abs.html

Dominik

> On Mon, 21 Oct 2002, Xavi wrote:
> 
> > Hello,
> > =A0
> > I believe that in R, it is not possible to analyze mixed effect-models
> > when the distribucion is not gaussian (p.e. binomial or poisson), isn't=
> ?
> 
> It depends on exactly what you mean.
> 
>  - Jim Lindsey's packages will fit (at least) random intercept models
> 
>  - For binomial or Poisson models with reasonably large means (perhaps 4
> or so) the PQL approximation used by glmmPQL in the MASS package is prett=
> y
> good.
> 
> > Somebody can suggest me alternative?
> 
> Again, it depends on why you want to fit mixed-effects models. You may be
> able to fit marginal models (GEE) instead.
>
> If you really want to fit mixed models with multiple random effects to
> binary data you probably need SAS PROC NLMIXED or a Bayesian solution
> (or HLM or MLWiN might be able to do it by now).
>
>	-thomas
Dominik Grathwohl 
Biostatistician 
Nestlé Research Center 
PO Box 44, CH-1000 Lausanne 26 
Phone: + 41 21 785 8034 
Fax: + 41 21 785 8556 
e-mail: dominik.grathwohl at rdls.nestle.com 


-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._