have you tried using glmer? If your dependent variable is poisson distributed, you can try something like fit<-glmer(y~x+(1|group), family=poisson)
and if you have differential exposure, you can do fit<-glmer(y~offset(log(exposure))+x+(1|group), family=poisson) Is this what you are asking? With regard to the t-statistics generated from lmer/glmer, you can get p-values by using dt(), or look at your confidence intervals for the parameters. Does this help? Corey ----- Corey Sparks, PhD Assistant Professor Department of Demography and Organization Studies University of Texas at San Antonio 501 West Durango Blvd Monterey Building 2.270C San Antonio, TX 78207 210-458-3166 corey.sparks 'at' utsa.edu https://rowdyspace.utsa.edu/users/ozd504/www/index.htm -- View this message in context: http://n4.nabble.com/Multilevel-modeling-with-count-variables-tp1692632p1693037.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
