The title says it all. I'm wondering if someone can help me understand the difference (if there even is one) between a Quasi-Poisson model and fitting a Poisson Regression Model using GEE? It is my understanding that both of these methods can be effective ways for handling over/under-dispersion and they seem similar, but I can't tell if they are the same thing or not.
I'm really surprised no one has addressed this? As often as I see the terms quasi-poisson and GEE used in the literature, maybe I'm not the only one confused by the seemingly dual usage of these terms?