[R] mixed effect-models

[Feng Zhang]

So in R there is no package for mixed models with multiple random effects to
Binary data?

Thanks.

----- Original Message -----
From: "Thomas Lumley" <tlumley at u.washington.edu>
To: "Xavi" <xpuig at dsss.scs.es>
Cc: <r-help at stat.math.ethz.ch>
Sent: Monday, October 21, 2002 9:03 AM
Subject: Re: [R] mixed effect-models


> On Mon, 21 Oct 2002, Xavi wrote:
>
> > Hello,
> >
> > 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 pretty
> 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
>
>
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