Hi,
I am dealing with a CMR data set with these characteristics:
- Individuals are marked, and a part of them sexed, by chicks (gender is determined only when they are first captured as chicks) at the breeding colony
- Observations are made at the breeding colony of individuals born there.
- 11 occasions throughout 13 years (two drought years with no breeding)
- Ca. 1/3 of captured individuals have been sexed.
I am interested in two analyses: one for estimating the apparent survival (survival*phylopatry) and the other to estimate the age of first breeding.
To do that I would implement respectively a CJS and a reverse time (Pradel) approach to estimate seniority (and derive probabilities of ages of first breeding).
I consider that gender is an important effect to test both on apparent survival and on seniority. For this reason, I wonder if there is a way to approach this without having to make data-censoring or splitting the data set in three groups (males, females, and unknown). I thought that perhaps I might prepare a data set for estimating apparent survival made of encounter histories with 4 events like these:
00100101000 1;
...
00000020200 1;
...
30003330003 1;
where 1=males, 2=females, 3=unknown.
I might do just the same by reverse encounter histories (for example in U-CARE) and use that file to estimate seniority as it would be a CJS (on reverse-time encounter histories). I might define a number of age classes that make sense according to the number of cohorts (10) and on a biological criterion and go on from there.
Question 1: does it make sense to use E-SURGE in this context? I am not sure at all, but in case it would, this is how I would configure pattern matrices.
Two steps process for Transition, a first one being Survival:
step1 (Survival)
s-*
-s*
--*
and a second one being Transition with parameters forced to be 1 like this:
step2 (Transition)
*--
-*-
--*
and a two steps process for Encounter
step1 (Capture)
*c-
*-c
*--
and:
step2 (State assignment)
*---
-a-*
--a*
Question 2: In case all of this made sense, would it make sense to estimate seniority this way?
Question 3: how should I define event two GEMACO sentences for both analyses if I wanted to consider a time and gender varying probability of state assignment?
The good part of this long post (sorry!) is that the answer might be very very short like answering “no” at question 1.
Thanks in advance for any help
Simone