On 7/28/06, Gregor Gorjanc <[EMAIL PROTECTED]> wrote: > Ben Bolker <bolker <at> ufl.edu> writes: > > ... > > I haven't tried it, but you could also consider using > > a Poisson-lognormal (rather than neg binomial, which is Poisson-gamma) > > distribution, which might make this all work rather well > > in lmer: > > > > www.cefe.cnrs.fr/esp/TBElston_Parasitology2001.pdf > > Actually it is very simple > > lmer(y ~ effA + (1 | effB), family=quasipoisson) > > i.e. this fits the following model > > y_ijk ~ Poisson(\lambda_ijk) > log(lambda_ijk) = \mu + effaA_i + effB_ij + e_ijk > effB_i ~ Normal(0, \sigma^2_b) > e_ijk ~ Normal(0, \sigma^2_e) > > Gregor
I would advise checking the results from lmer against those from another way of fitting this model or the negative binomial model. There may be a problem in the way that lmer handles the scale parameter. I haven't checked generalized linear mixed models with a scale parameter as extensively as I have checked those without a separate scale parameter (the binomial and Poisson families). If anyone can provide me with an example of such a model and sample data (preferably off-list) I would appreciate it. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.