by darryl » Sun Oct 05, 2008 4:37 pm
Completely appropriate, you just have to determine what your effective sample size is for these models.
We can come up with a number of reasonable definitions based on deep thought and comparison with other models. At the time of writing the book, we couldn't decide (and still really haven't) what the 'right' number might be, so took the ostrich approach and kept our heads in the sand over the issue.
Options are:
1. Number of sampling units
2. Number of detections (equivalent to number of releases in CJS)
3. Number of surveys at 'occupied' units
4. Something else
I've ranked these in order from conservative -> liberal, meaning that with option 1 you're going to get the greatest penalty for more complicated models resulting in the simpler models getting ranked too high if the real ESS is actually something bigger. Probably not a bad property oftentimes, but not always. I tend to suggest that people try a couple of options if they're concerned and see how that effects final inferences.
Darryl