Hello,
I am working on a survival analysis and have successfully built and run the necessary models using RMark, however, am having issues with model averaging using both the RMark package and with the program MARK interface. Due to how the data were collected I'm using a nest survival model broken into monthly intervals allowing me to produce estimates of monthly survival rates. All of the variables included in my models are categorical. The variables include year (2007, 2008, 2009, 2010, 2011), season (breeding, summer/fall, and winter), reproductive status (successfully nested or did not successfully nest), age class (adult or yearling), and study area (3 different study sites).
Year and season appear to be two of the most important variables, but since there is not a single model that received overwhelming support (model weight for the top model is 0.23) it seems model averaging would be appropriate. I would like to get model averaged results for the average monthly survival rate during each year and then separately the monthly survival rate during each season The problem that I am running into is that rather than obtaining a model averaged survival rate during each year or during each season I am getting model averaged results for each different combination of covariates (e.g. 2007 - breeding season - successful nest - study area 1, 2007 - breeding season - unsuccessful nest - study area 1, 2007 - breeding season - successful nest - study area 2, 2007 - breeding season - unsuccessful nest - study area 2… And the list goes on).
I understand how to use model averaging with individual covariates such as body mass or wing chord but am falling short when trying to model average with group covariates. Is there a way to produce model averaged results with group covariates that does not return a model averaged survival estimate for each combination of groups but only for the variables of interest (e.g. year or season)? Any advice or suggestions would be greatly appreciated.
Thank you,
Joel