We consider capture-recapture studies where release and recapture data
are available from each of a number of strata on every capture occasi
on. Strata may, for example, be geographic locations or physiological
states. Movement of animals among strata occurs with unknown probabili
ties, and estimation of these unknown transition probabilities is the
objective. We describe a computer routine for carrying out the analysi
s under a model that assumes Markovian transitions and under reduced-p
arameter versions of this model. We also introduce models that relax t
he Markovian assumption and allow ''memory'' to operate (i.e., allow d
ependence of the transition probabilities on the previous state). For
these models, we suggest an analysis based on a conditional likelihood
approach. Methods are illustrated with data from a large study on Can
ada geese (Branta canadensis) banded in three geographic regions. The
assumption of Markovian transitions is rejected convincingly for these
data, emphasizing the importance of the more general models that allo
w memory.