Tracy Feldman <tracysfeldman <at> yahoo.com> writes: > > To whom it may concern: > > I have a question about how to appropriately conduct an lmer analysis for negative binomially distributed > data. I am using R 2.2.1 on a windows machine. > > I am trying to conduct an analysis using lmer (for non-normally distributed data and both random and fixed > effects) for negative binomially distributed data. To do this, I have been using maximum likelihood, > comparing the full model to reduced models (containing all but one effect, for all effects). However, for > negative binomially distributed data, I need to estimate the parameter theta. I have been doing this by > using a negative binomial glm of the same model (except that all the effects are fixed), and estimating mu > as the fitted model like so: >\
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 cheers Ben Bolker ______________________________________________ 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.