Hi everyone,
I’m trying to use multi-state models to answer the simple question of whether survival in state A differs from state B, but I have data that are best described as “live capture and release” plus “resight” data.
Example:
Summer breeding (state A) and summer non-breeding (state B) birds
Sampled twice per year for 5 years, in breeding and in wintering season (same geographic location)
Winter captures coded as a “resight” because breeding state cannot be coded during winter but these captures offer information about survival
Want survival estimates for breeding and non-breeding states (SA and SB)
After much RTFM (and primary lit and forum posts) and many analysis forays, I selected a multi-state Barker model as the best choice for my particular dataset. However, I immediately got the error that this model is restricted to “AB01” data and does not accept “2” as a resight code, as the other Barker models do.
Is there really no way to include my out-of-season “resight” data in a multi-state model? Is there a workaround? A better model class choice? Any and all suggestions are welcome and appreciated.
Reducing the dataset to only “in-season” observations results in giant error estimates, but the only other workaround that I can even halfway justify is coding out-of-season captures as “non-breeding” and hoping that allowing time variation in transition probabilities will take care of the uneven distribution of states among sampling encounters (but unfortunately I can’t use a primary/secondary setup in a robust design because that produces the error that you can’t have both states A and B within a single primary).
I’m sure that someone out there has dealt with a similar situation before - any advice from you wise experts is greatly appreciated, and a giant thank you in advance!
Cheers,
ardr
P.S. More specifics on my sampling design/dataset/study organism (which is not actually a bird, or breeding, but was nicely analogous to this example used in the MARK book) happily given upon request.