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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