I originally asked this question on Stack Overflow and Stack Exchange, going to try my luck here this time. I'm trying to model the number of parks in a neighborhood as a function of education, land area (both continuous variables), and poverty percentage (categorical). There may be other covariates included but for the sake of the question I will exclude them for now. I chose a Poisson model because to my understanding this is the model that is ideal for count data and my data has a lot of sampling zeroes. My unit of analysis for the neighborhood is the census tract. Using ArcGIS, I joined geocoded point information about parks to a census tract shape file, exported this information into SAS, and generated counts. I then ran the following Poisson model. proc genmod data = parks; class povper / descending; model cnt = povper edu area / link=log dist=poi; run; My issue with this model is that it doesn't take into account the number of parks in neighboring census tracts. I've been reading about possibly creating a spatially lagged dependent variable, but according to this answer, spatial lag and poisson don't necessarily mix. All of the census tracts in my table have x/y coordinates. Does anyone have advice on how I could incorporate the park counts from neighboring census tracts into my model using SAS?
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