Hello,
I am currently running a multi-state model using RMark (a package in R that calls upon Program MARK) and using U-CARE to assess goodness of fit. I am studying how survival and movement of humpback chub vary spatially along the Little Colorado River, which is a tributary to the Colorado River. The ‘states’ in the model correspond to sites along the Little Colorado River. There are three sites: Boulders (the most downstream), Coyote (mid-stream), and Salt (the upstream site). I had a few questions concerning using U-CARE to assess goodness of fit and estimate c-hat:
Q1: I can’t seem to figure out how to account for unequal time intervals in U-CARE. I’m not sure whether it’s important to account for unequal time intervals for any of the chi-square GOF tests.
Q2: My initial results (that don’t account for unequal time intervals) show that Test 3G is close to significant (p=0.06), indicating there might be transience in the population. When I look at the individual tests, this result seems to be driven by Boulders site, which has p-values< 0.05 for both 3G.R and 3G.M. Boulders site is adjacent to the Colorado River, and it is therefore not surprising that fish sampled at this site have a higher probability of emigration from the study area. Furthermore, estimates of apparent survival are lower at Boulders site compared to the other two sites. Here are my options as I see it:
1) Keep the current parameterization of the model (that does not include an effect for transience), and say that the differences in apparent survival among sites might be influenced by increased emigration at Boulders site.
2) Restructure the model to account for transience at Boulders only.
3) Restructure the model to account for transience at all sites.
I don’t really know if 2) or 3) are options because this model only has two “cohorts.” In other words, we only marked fish in the first two sampling occasions, with the remaining four occasions used for recapture information only. Thus, occasion 2 is the only time when both newly marked and previously marked individuals are both present in the population. Since there is no way to estimate ‘p’ for newly marked fish during occasion 2 (this model is fully parameterized for capture probability), I can’t really think of a good way to compare capture probabilities for newly marked and recaptured fish during occasion 2.
Thanks,
Maria