[R] mixed effects models - negative binomial family?

Prof Brian Ripley ripley at stats.ox.ac.uk
Mon Jan 2 19:19:19 CET 2006

On Mon, 2 Jan 2006, Ben Bolker wrote:

> Constantinos Antoniou <antoniou <at> central.ntua.gr> writes:
>> Hello all,
>> I would like to fit a mixed effects model, but my response is of the
>> negative binomial (or overdispersed poisson) family. The only (?)
>> package that looks like it can do this is glmm.ADMB (but it cannot
>> run on Mac OS X - please correct me if I am wrong!) [1]
>> I think that glmmML {glmmML}, lmer {Matrix}, and glmmPQL {MASS} do
>> not provide this "family" (i.e. nbinom, or overdispersed poisson). Is
>> there any other package that offers this functionality?
> You'll probably get more complete/informed information
> shortly, but ... you may not be able to get a negative
> binomial distribution per se, but other versions
> of "overdispersed Poisson" are indeed possible.  glmmPQL
> will let you use the quasipoisson family, which allows for
> overdispersion in a phenomenological way;

and has worked examples of this in the book it supports.

It also lets you use a negative binomial family, and MASS provides one.

> more mechanistically,
> observation-level random effects on the scale of the
> linear predictor (log for a GLMM with family=poisson)
> lead to a lognormal-Poisson distribution, which has similar
> properties to the NB.  I suspect you can do this in lmer
> (lme4 package), which does GLMMs if you specify the family
> argument.
> See:
> http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11393830&dopt=Abstract
> (analysis done in SAS but probably completely feasible in R at this point)

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 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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