Diff occ est if IC in file vs not in file, even if not used

[maryconner1]

Greetings:
I am running a 32 year occupancy data set for spotted owls, which has 1 group and 14 surveys per year (448 enc) using the robust occupancy formulation with psi(1), gamma, and epsilon. When I run the data WITHOUT an IC in the file I get reasonable occupancy estimates that are greater than the naïve estimates.

However, when I append ICs to the file (there are 448 IC, each representing whether there was reproduction noted on each visit) I get different lower estimates. These estimates are less than the naive estimates, which is not correct. Note that I used the global model psi0 e(yr) g(yr) p(year*survey) for both cases (so I did not use an IC in the model).

I also tried the psi, epsilon formulation, but got the same results.

To determine if the problem were too many ICs, I created 1 dummy IC and attached it to the data file and re-ran the same global model (not using the IC). Again the estimates were lower than the run without an IC in the file, and lower than the naive estimate.

There are lots of missing values in the data (dots for not surveyed), but no missing values for the IC (it was noted for every survey that occurred).

Thanks for your consideration of this issue (I hope I'm being myopic and it's something easy). Mary