## Robust Design and Ages

Forum for discussion of general questions related to study design and/or analysis of existing data - software neutral.

### Robust Design and Ages

Hello All,
I've searched for a similar question but I couldn't seem to find any so here it goes....
For my data, an analysis of small mammal populations, I have been using a robust design model in RMark. I have 6 primary periods with 3 secondary periods each. I had the covariates sex, species, and treatment levels. My adviser now wants to add age as a covariate. At first, I thought this would be straight forward but because small mammals mature quickly, I have individuals that start as a juvenile and are adults by a different primary period. Is there an easy( lol nothing easy but logical) way to add this to the robust design model? I saw in chapter 7 of a gentle introduction that it is normally done with a cjs model a specific order of the PIMS but the way my data was collected was for a robust design model. I would greatly appreciate any tips or ideas, thank you in advance.
jln1234

Posts: 5
Joined: Tue Sep 01, 2020 2:34 pm

### Re: Robust Design and Ages

This is a solvable problem, but it depends on what age is meant to predict. If it's survival or temporary emigration, then you would do it the same way that you saw with the CJS model (2 groups: first captured as juvenile and first captured as adults). The first diagonal of the PIM for the young would be unique, but the rest of the PIM would match with the PIM for the adults (see chapter 7 of the book). The first diagonal applies to the first survival (primary period) interval after initial capture. After that initial interval the individual is now an adult, and therefore parameters for that group match with the group for released as adult.

If you want to model detection probability as a function of age, then I believe you could do it with a time-varying individual covariate on p/c (e.g., a 1 for the primary period when they are juveniles to offset them from adults, and a 0 when they are adults). Alternatively, you could do the entire analysis using the multistate robust design model, defining a juvenile state and an adult state. Those that start off as juveniles transition to adults with probability 1.0. If you also have temporary emigration (unobservable states), then your state structure would be more complicated but still doable.
Bill Kendall

Posts: 86
Joined: Wed Jun 04, 2003 8:58 am

### Re: Robust Design and Ages

Thanks for getting back to me!
I have a few follow-up questions and aspects I would like clarified just to make sure I understand. The age would be to look at survival. So going back and reading through chapter 7, I would organize my encounter history with individuals who were first marked as juveniles or first marked as adults. So the encounter history would look like
Code: Select all
`100100001111111111 A Bla B Perm. F`
or
Code: Select all
`100100001111111111 J Bla B Perm. F`

or with A representing adult and J representing juvenile. Or would it be best to have that in 1s and 0s? My next question is how do I actually incorporate that into the robust design in RMark? Looking at the Crmark section in the gentle introduction it looks like I would make it a design covariate then use add.design.data? The example uses bins? Would I then create bin 1 and 2 ( one for adult and the other for juveniles). If that is the way to do that in Rmark how does that tie into creating the PIM tables from chapter 7. I apologize for the bombardment of questions and clarifications.
jln1234

Posts: 5
Joined: Tue Sep 01, 2020 2:34 pm

### Re: Robust Design and Ages

At this point, this is (rapidly) morphing into an RMark question, so I'm going to split this thread, and move the last post, and those following, to the RMark subforum.
egc