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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