Dear R users,

I work with a descrete variable (sclae 0 - 27) which is highly skwed to the right (many zeros and small numbers). I measure this variable on a control and intervention cohort 5 times a year. When I analyze analyze this varoable at each time point separately and use GLM with family quasi-Poisson (descrete outcome and two binary variables, gender and cohort, are predictors), I observe an overdispersion. When I use GEE with R software, does GEE R package takes care only about over-dispersion regarding the repeated measure design  per se, or it takes care about the over-dispersion within the cohort as well which I observe with GLM method when I choose quasipoisson family? If so what options in GEE should I use to control both types of overdispersion?  I need to take care about the double effect of overdispersion (related to repeated measures and within cohort overdispersion) and wonder how GEE package takes care about it.

Thank you very much for you help and ideas!

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