Multiple and generalized random effects models in MARK

[jlaufenb]

I'm interested in conducting a variance components analysis and fitting random effects models in a mark-recapture framework with model structure differing (e.g., no intercept vs linear trend) by group (e.g., male and females) and parameter (e.g., phi and f) using the robust design Pradel data type in MARK. I have extensively searched the literature for information on fitting these types of random effects models using MARK. The only reference to this approach is a comment made by Burnham and White (2002),

"What of the future of multiple and generalized random effects in capture-recapture models, such as to males and females jointly with correlated random variation? It is bright, but probably not to be much found in moment-type equations...".

Is fitting these types of models possible in MARK or must a different route be taken? If so, how can it be done? If not, can anyone suggest how to do it otherwise?

Thanks
Jared

[cooch]

I'm interested in conducting a variance components analysis and fitting random effects models in a mark-recapture framework with model structure differing (e.g., no intercept vs linear trend) by group (e.g., male and females) and parameter (e.g., phi and f) using the robust design Pradel data type in MARK. I have extensively searched the literature for information on fitting these types of random effects models using MARK. The only reference to this approach is a comment made by Burnham and White (2002),

"What of the future of multiple and generalized random effects in capture-recapture models, such as to males and females jointly with correlated random variation? It is bright, but probably not to be much found in moment-type equations...".

Is fitting these types of models possible in MARK or must a different route be taken? If so, how can it be done? If not, can anyone suggest how to do it otherwise?

Thanks
Jared

This should be in the MARK subforum, so I'm going to move it there.

As to your question, Appendix D.

[cooch]

I have extensively searched the literature for information on fitting these types of random effects models using MARK. The only reference to this approach is a comment made by Burnham and White (2002),

BTW, the next time you 'extensively search', I'd suggest searching the forum, and the book as part of your 'extensive' search.

This is a MARK FAQ, which you also might want to read -- viewtopic.php?f=39&t=9

See in particular items (5) and (6).