I agree with David. A dispersion parameter of 25 suggests that you have mainly 0's in your data set and your model is not adequate. Perhabs you should dichotomize your data in 0 and 1's and use a logistic mixed model but be aware of small numbers of events.
That amount of overdispersion would make the use of a poisson model very questionable, and will very likely result in estimated standard errors that are too low, hence the change in statistical significance when you switch to quasipoisson. O -- View this message in context: http://www.nabble.com/dispersion_parameter_GLMM%27s-tf3354683.html#a11810939 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
