[R] writing a package for generalized linear mixed modesl

Prof Brian D Ripley ripley at stats.ox.ac.uk
Fri Apr 12 11:32:53 CEST 2002


On Fri, 12 Apr 2002, juli g. pausas wrote:

> Hi,
>
> I think that "reglm"  fits GLM with random effects in S (see
> http://www.statsci.org/s/reglm.html).
> In fact I was looking for a R equivalent of reglm, but I didn't find it.

Look at glmmPQL as detailed below.  It's not the `equivalent of reglm', but
it does what reglm does, and much besides.

I looked at porting reglm to R, but its style is so inefficient S it
appeared to be better to rewrite it from scratch.  In the end I wrote code
for a more powerful approach.

>
> Juli
>
>
> On Mon, 1 Apr 2002, Jason Liao wrote:
>
> > Happy new month, everyone!
> >
> > I am planning to write a NIH grant proposal to study ways to speed
> > Monte Carlo based maximum likelihood algorithm for hierarchical models
>
> > with a focus on generalized linear mixed models (GLM with random
> > effects). I thought it would be nice and also increase the chance of
> > funding if I could produce an R package in the process. I understand
> > that Prof. Pinheiro ang Bates have produced LME for linear mixed
> models
> > and NLME for non-linear mixed models. But these do not fit logistic
> > mixed models or Poisson mixed models. SAS Proc NLMIXED can fit simple
>
> GLME (beta, S-PLUS only) does.
>
> > logistic or Poisson mixed models but the syntax is not specific for
> > generalized mixed models. There can be only one level of random
> > effects. STATA version 7 can fit random intercept models but not more.
>
> > There are also some standalone programs such as MIXOR by Don Hendeker
> > of Chicago. But it is hard to use a stnadalone program for data
> > analysis efficiently because you have to convert the data set and you
> > lose all the familiar tools for data transformation and graphics.
> >
> > I would appeciate your comments on the following points:
> >
> > 1. Is there a strong need for a package for generalized linear mixed
> > models? Could someone have already written or in the process of
> writing
> > one?
>
> See package GLMMgibbs on CRAN, function glmmPQL in package MASS and
> function glmm (only a random intercept) in one of Jim Lindsey's
> packages.
>
> GLMMs are half a chapter in the upcoming fourth edition of Venables &
> Ripley.
>
> > 3. How big is the undertaking? I have some R code for GLMM that runs
> at
> > an acceptable speed. I can see that some part can benifit from
> > converting to C or Fortran. I am not familiar with R's interface with
> C
> > and Fortran. I do not know either how to make the package available
> for
> > different platforms. Will the multi-platform issue become easier if I
> > stay with 100% pure R?
>
> 100% pure R would be unacceptably slow.
>
> I would rate this as a research problem, and a major undertaking.
> GLMMgibbs is an existence proof, but not able to handle many quite
> simple
> problems.
>
> --
> 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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-- 
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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