[R-sig-eco] AIC, R-Mark, and nest survival

[Jessi Brown]

Hi, Dave. Thanks for pointing out the merits of R-Mark as far as 
generating AIC tables reflecting the results of nest survival and other 
data model types.

I do indeed use R-Mark for CJS and multistate population modeling, but I 
prefer the logistic exposure/"Shaffer" nest modeling paradigm for a 
number of reasons. When you have something of a background in linear 
models, the GLM approach is perhaps a little more intuitive than Program 
MARK (but R-Mark circumvents some of that), and data preparation and 
covariate handling seems to go more quickly and easily. Plots in R come 
out so nicely, publication quality if you specify them correctly. Also, 
there's capacity for extending the logistic-exposure models to mixed 
models (which might not be a wise decision, based on violation of the 
assumption that the mean of the error distribution is equal to zero, but 
I digress).

I've done nest survival with both Program MARK (not R-Mark) and GLMs in 
R, and it seems to me (not a biostatistician, but an ecologist who 
dabbles with statistical tools), that it's ok to just go with whatever 
suits your particular style. In my case, since I tend to start with (and 
retain) fairly focused, restricted model suites, it doesn't bother me 
much to hand construct AIC tables with the "n-effective" calculated AIC 
values after having run the GLMs.

BTW, if anyone needs a script of how to set up the logistic-exposure 
link function, it's among the examples in help(family).

cheers, Jessi Brown

-- 
Jessi L. Brown
Ph.D. Student, Program in Ecology, Evolution, and Conservation Biology
University of Nevada, Reno

1000 Valley Rd.
Reno, NV 89512
jlbrown at unr.edu