[R] Help to conduct a random factor analysis with binomial response
vito.muggeo at giustizia.it
Wed Nov 21 12:07:30 CET 2001
Estimation of GLMM is also implemented in statmod library (reglm() function,
it should be) by Smith for S+ (unfortunaly I don' t remember the web page)
that uses the method decribed in Schall (1991).
This method is substantially a PQL, isn't it or am I wrong?
Dear Prof. Ripley, were can I find your wrapper around lme that fits GLMMs
by PQL? maybe can you send me it? Thank you
----- Original Message -----
From: "Prof Brian Ripley" <ripley at stats.ox.ac.uk>
To: "Douglas Bates" <bates at stat.wisc.edu>
Cc: "Leif Egil Loe" <l.e.loe at bio.uio.no>; <r-help at stat.math.ethz.ch>;
<atle.mysterud at bio.uio.no>
Sent: Tuesday, November 20, 2001 6:58 PM
Subject: Re: [R] Help to conduct a random factor analysis with binomial
> On 20 Nov 2001, Douglas Bates wrote:
> > Leif Egil Loe <l.e.loe at bio.uio.no> writes:
> > > I am a ph.d. student in biology working on red deer in Norway, who
> > > would like to conduct an analysis with random factor where the
> > > response is binomially distributed. This cannot be conducted in
> > > S-plus, and I was told by others that it may be possible in
> > > R. However, I soon got into trouble which I hope you can help me to
> > > solve.
> > This type of model is a generalized linear mixed model.
> > I think you would have to use the GLMMGibbs package in R to analyze
> > it. You can't fit this type of model with the nlme package in R or in
> > S-PLUS.
> Since there was just a single additive random factor, another alternative
> is another glmm() in one of Jim Lindsey's packages (gnlr, I think).
> I had a student exploring some of these over the summer, and there were
> lots of problem getting GLMMGibbs' glmm to keep running with binary
> responses (it got internal errors), and a couple of times Lindsey's glmm
> gave (practically) different answers to all other methods.
> There will soon be some alternatives. I have a wrapper around lme that
> fits GLMMs by PQL, and that is working in R and S-PLUS. It will make the
> MASS library soon, and I can make beta versions available. (For S-PLUS
> Jose' Pinheiro has at alpha/beta a more sophisticated wrapper called GLME,
> but that depends on the very latest S-PLUS version of NLME). James
> McBroom and I have at alpha stage an adaptively tilted numerical
> quadrature method that seems to do ML fitting fast and accurately thus
> There are some alternatives for S code for PQL about, too, although
> those I have seen are none too flexible.
> We (James and I) would be happy to try out what we have on the deer data
> for you.
> Brian D. Ripley, ripley at stats.ox.ac.uk
> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
> University of Oxford, Tel: +44 1865 272861 (self)
> 1 South Parks Road, +44 1865 272860 (secr)
> Oxford OX1 3TG, UK Fax: +44 1865 272595
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