I'm currently conducting an analysis of seasonal survival in RMark using Burnham's joint analysis model. The year is broken into the non-breeding season (Sept. - April) and the breeding season (May-August). Capture periods occur in May, June, and August, so that the breeding season is divided into 2 intervals (mid-May to mid-June and mid-June to late August) and the non-breeding season is a single interval from September to April. In MARK I could go into the PIMS and 'constrain' the 2 intervals of a breeding season to have the same survival, but I can't figure out how to do this in RMark. It seems that adding a factor for breeding season and non-breeding season may be the only way to do this. This would require a new factor for each model of interest (e.g., nbs(.) bs(.) vs. nbs(t) bs(t)) - I wanted to see if there were other options before going further. Any ideas would be appreciated. Thanks, Jeff Warren Wildlife Biologist Red Rock Lakes NWR Lima, Montana 59739 (406) 276-3536
RMark Burnham Ananlysis
2 messages · Jeffrey_Warren at fws.gov, Jeff Laake
Best place to post questions about RMark is on the phidot MARK forum. I do get postings from this list but in digest form but I don't always review carefully. Also, since RMark is not on CRAN many on this list may not be aware of RMark. Now to your question. You are on the right track to add another factor variable but not for groups. I didn't quite understand your notation but you need to add a factor variable to the design data for S that you can use in place of the default time field. I don't know how you have your time intervals set up but let's say it is something like below where time starts at beginning of "year" and end of breeding is after .2 of a year (not sure arithmetic is correct here). Because S is an interval paramter, time will be given the value of the beginning of the interval. Thus, records in the design data with values of 1.0,1.1,2.0,2.1 etc are breeding season periods and the periods 1.2,2.2,... will be non-breeding periods ddl$S time 1.0 breeding 1.1 breeding 1.2 non-breeding 2.0 breeding 2.1 breeding 2.2 non-breeding . . So you can create 2 factor variables. One could be B or N for breeding non-breeding that would allow you to fit a model with differences between seasons but not years and the other would be Year which would be for yearly effects. You could do this as follows if your design data is names ddl: ddl$S$season="B" ddl$S$season[ddl$S$Time-floor(ddl$S$Time)>0.15]="N" ddl$S$season=factor(ddl$S$season) ddl$S$year=factor(floor(ddl$S$Time)) Then you can use models for S like ~season, ~year, ~season+year or ~season*year where the latter is equivalent to ~time. Note that I didn't check the above in R and you'll want to modify to fit your time setup but it should get going in the right direction. --jeff