Hi all, I am having some trouble running GLMM's and using model averaging with QAICc.
Let me know if you need more detail here: I am trying to run GLMM's on count data in the package glmmADMB with a negative binomial distribution due to overdispersion. The dispersion parameter has now reduced to 2.679 for the global model (from a dispersion parameter of 27.507 with a poisson distribution), and I am not sure if this is still considered too high for running the models? I would like to try to use QAICc's for model selection and model averaging with the package MuMIn. I have so far been able to produce a QAICc output only for the models. I read that model averaging with QAICc can be done in MuMIn but cannot find the syntax to get these outputs, including the model weightings, parameter estimates, confidence intervals, and relative variable importance. Any advice would be greatly appreciated. As well as if there are other potential better options for dealing with the overdispersion. Thank you in advance, Diana [[alternative HTML version deleted]] ______________________________________________ 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.