I'm analyzing social network data where roughly 10 groups of 100 people are split into different sized teams. (For example, there are 10 schools, but some of the schools have 5 "classrooms" while other schools have "15 classrooms")
Let's say each student is a node. I'm interested in the number of distinct classrooms that each student interacts with in a week. In particular, I'd like to model the effect of # of teams on the # of distinct classrooms interacted with.
I was thinking about using the poisson family for a generalized linear function. (I thought poisson was appropriate because it is count data over a limited amount of time.)
However, I realize that there is a natural upper limit. No student can interact with more classrooms than are present at their school. Could I still use the poisson and take this into account?