I’m new to MARK, and while the manual is well written, I am still a touch confused with regard to the estimable parameters of a CJS with individual covariates.
For clarity, I’ll ask the question using a ‘dummy ’ dataset, with 4 encounter occasions, 1 group and 1 covariate.
With a basic CJS (i.e. no CoVar’s), and a fully time dependent model, I understand that would have 5 estimable parameters (Phi 1, Phi 2, p2,p3 and the product of Phi3*p4). The design matrix would have 6 columns.
If I incorporated a simple covariate (i.e. mass), and ran the model Phi (t + mass) p (t), with different INTERCEPTS and a common SLOPE, how many estimable parameters would there be? In the DM, there would be a total of 9 columns, but does the non-estimability of the product of Phi3 * p4 affect BOTH the ‘dummy’ coding column and the CoVar coding column for Phi 3?
I hope this makes sense. Any help at all will be appreciated!