Thanks Ballardw! In the first case, I think I'd "merge" with the (a) geographically more proximal of the two, or (b) the one with the smaller sample size (90100). In the second case, the two groups of 3 with code 9010X would ultimately be collapsed into a single group with a size of 6, since none of those individual zips can stand alone. I don't have any zip+4 codes - they are all just straight zips. I used Proc SQL to build the summary dataset, and could definitely start by sub-setting to just those zips that are going to be a problem. I am a little concerned about the geographic contiguity issue, but I don't really know how to best deal with it. I'm sure there's some way to write a script that can preferentially merge proximal areas, but I don't know how to do that.
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