Are you trying to fit a Poisson GLMM with Gamma random effects? I don't think you can do that using (g)lmer, which assumes a Gaussian distribution for the random effects. You might have a look at the hnlmix function in Jim Lindsey's repeated package. Or you could use Bayesian methods in JAGS, BUGS etc. Usually Gamma random effects are multipliers, not additive. So it makes sense to set the mean =1, unlike Gaussian random effects with mean=0. This will place a restriction on the shape and scale parameters.
HTH, Simon. On Sun, 2008-08-24 at 22:10 -0400, Robert A. LaBudde wrote: > I'm trying to figure out how to carry out a Poisson regression fit to > longitudinal data with a gamma distribution with unknown shape and > scale parameters. > > I've tried the 'lmer4' package's glmer() function, which fits the > Poisson regression using: > > library('lme4') > fit5<- glmer(seizures ~ time + progabide + timeXprog + > offset(lnPeriod) + (1|id), > data=pdata, nAGQ=1, family=poisson) #note: can't use nAGQ>1, not > yet implemented > summary(fit5) > > Here 'seizures' is a count and 'id' is the subject number. > > This fit works, but uses the Poisson distribution with the gamma > heterogeneity. > > Based on the example in the help for glmer(), I tried > > fit6<- glmer(seizures ~ time + progabide + timeXprog + offset(lnPeriod) + > (1|pgamma(id, shap, scal)), data=pdata, nAGQ=1, start=c(shap=1, scal=1), > family=poisson) #note: can't use nAGQ>1, not yet implemented > summary(fit6) > > but this ends up with "Error in pgamma(id, shap, scal) : object > "shap" not found". > > My questions are: > > 1. Can this be done? > 2. Am I using the right package and function? > 3. What am I doing wrong? > > Any help would be appreciated. > > Thanks. > > ================================================================ > Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: [EMAIL PROTECTED] > Least Cost Formulations, Ltd. URL: http://lcfltd.com/ > 824 Timberlake Drive Tel: 757-467-0954 > Virginia Beach, VA 23464-3239 Fax: 757-467-2947 > > "Vere scire est per causas scire" > > ______________________________________________ > R-help@r-project.org 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. -- Simon Blomberg, BSc (Hons), PhD, MAppStat. Lecturer and Consultant Statistician Faculty of Biological and Chemical Sciences The University of Queensland St. Lucia Queensland 4072 Australia Room 320 Goddard Building (8) T: +61 7 3365 2506 http://www.uq.edu.au/~uqsblomb email: S.Blomberg1_at_uq.edu.au Policies: 1. I will NOT analyse your data for you. 2. Your deadline is your problem. The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. - John Tukey. ______________________________________________ R-help@r-project.org 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.