dfowler wrote:Hi,

I am looking to evaluate heterogeneous survival in a model across groups and time.

There are several different approaches to handling heterogeneity in MARK -- you mention the finite-mixture approach, but you might want to consider the logit-normal approach based on numerical integration of the individual RE. There is growing evidence that it is actually more robust than the finite mixture approach.

Is it possible to develop a finite-mixture survival model (based on Pledger mixture Seber recoveries in RMark) that provides mixture proportions (pi) that are time and group dependent? Currently, I am aware of the capability to model mixed survival as group and time dependent but the output provides only a constant mixture proportion. Is there a straightforward path to estimating time-dependent proportions of the mixtures?

Estimates of the mixture parameter,

, are generally not interpretable. Using such mixture models gives you more robust estimation of other parameters, but the mixture parameter should not be interpreted, per se. Also, you can estimate a mixtures within groups, but not a temporally varying mixture parameter.

Secondly, what can I correctly interpret from the time and/or group dependent mixtures? In a two group mixture, can the proportions be a biologically interpretation of population structure?

See above -- generally, nothing. Shirley Pledger (being the person who has done the most work with mixtures) strongly advises against it (in fact, this was one of the messages of her plenary at the most recent EURING meeting). See various sections in Chapter 14 of the MARK book, where mixture models are introduced.