I'm working on a project that involves count data (specifically number of interactions) from multiple different districts in a specific area. Our team has been talking about calculating a few different centrality measures (degree centrality, closeness centrality) of the networks in the different districts. Due to limitations in our design, the nodes from different districts do not overlap in their interactions; basically, someone from district A did not ever interact with someone from district B in our data. If we are trying to see how network metrics may be affected by demographics (let's say age for example), does it make sense for us to create one model of the entire area for how certain network characteristics affect an individuals network metrics? Or should we create models of each individual network? I've heard some of these network metrics are affected by size so I imagine there might be a problem with treating these metrics as the same thing when their networks(districts) vary greatly in size.