by abreton » Tue Mar 25, 2008 1:33 pm
If you are interested in estimating recruitment then it does not make sense to even consider the parameterization (phi, p) specified by the CJS model. And note that even if you did fit your data to the CJS and Pradel reverse-time/recruitment models, the AIC values would not be comparable since the likelihoods specified by these models are inequivalent. Similarly, AIC values from the Jolly-Seber (includes recruitment) and Pradel models cannot be compared - see the MARK help file under Pradel > Recruitment Parameters for more information.
I wonder if you wrote 'CJS' but meant 'JS' (Jolly-Seber)? Certainly, the Pradel model discussed here and JS are in the same class of models so you should consider the strengths and weaknesses of each of these given your data along with others including the Link-Barker parameterization (see losses on recapture under Pradel > Recruitment Parameters in MARK help file). I recommend that you read through Chapter 18 in Williams et al. "Analysis and Management of Animal Populations" and Chapters 13-14 in a Gentle Intro to Mark if you haven't done so already. Rather than use the best JS model as a template to build our starting Pradel model (e.g., sex but no presence fitted to survival), it seems more logical, given the important differences between these two models, to decide which model type (from this class of models) is best given your data and then use it exclusively in your analysis.