I am working on a large dataset for Tasmanian devils. For each individual we have the following covariates: sex, age (2 levels), disease (yes/no). There are no missing covariates so I am using the conditional likelihood model to include individual covariates. The highest ranking model includes disease and age as a covariate for g0 and age as a covariate for sigma which makes sense. I then use derived() to estimate group specific densities. As part of the analysis of this dataset we are interested in estimating the true percentage of diseased animals and animals in each age class for each session accounting for differences in capture probability. However, when I look at the density ratios estimated by derived they are the same as he ratios for the captured individuals which is not logical given the difference in capture probability. Is there something I am missing?
Thanks,
Mathias
- Code: Select all
secr.res<-secr.fit(capthist=capthist ,model = list(g0~disease+age+Site,sigma~age+Site),sessioncov=sessioncovdata, buffer=buffer,binomN = 1, detectfn = 'HN',CL=T,start=secr.0)
pred<-derived(secr.res,groups=c("age","disease"))