Hi Bruce,

I think it's okay to keep patch size as continuous. My initial concern (and I haven't figured out yet if it's valid) is that if patch is a random factor, you have to specify it in the model, but the patch size, which is also in the model as an IV, would be confounded (since each patch size has only one patch). If patch size is categorical, there will be multiple patches per size.

Anyway, you have a 3 level model, since each there are multiple transects per patch and two visits per transect. You have two further complications. 1. some patches have only one transect (no variance for that patch) and 2. your DV is not normally distributed. Whether you use a binary or count DV, you're talking either logistic or Poisson regression. Either way, you have to use GEE, not regular mixed models theory. I'm not completely up on this off the top of my head, but there are limitations in GEE. I don't know if it's just software limitations or GEE theory, but I think it's tricky beyond a two level model.

Which software do you use? It might affect your options for how you analyze it. I am most familiar with SAS for mixed models, including GEE, but I believe that Stata has more flexibility in what it can do.

Karen