Ok, I think I have things figured out. Predict.glm still doesn't work (with type="response"); however, the problem with the strange behavior of the betas and the results of predict.glm with type="link" was simply due to data issues. I had converted my Program MARK input file (which needs only three piece of information; age of nest at start, age of nest when last alive, and age of nest when observation ends) directly to a data matrix. Therefore, the successful nests were "observed" for only one interval (age of nest when last alive=age of nest when observation ended), and during that interval, their mean age was around 34 days (since the nest cycle lasts 68 days). Those nests that failed later were forced into a second interval that had a later mean nest age. So the glm's were performing as expected from the data supplied.
So, I went back to the original nest site visitation data and broke those 68 day intervals (as well as all others) into the much shorter, original visitation intervals. And now the resulting daily survival rate estimates are more believable, corresponding well to the equivalent Program MARK output. I think (correct me if I'm wrong, Mark) that the only detail left to examine is the true "effective" sample size for use when calculating AICc values, as each observation interval does not comprise an independent observation. That is apparently easily done by hand, but would be convenient to include in a future "avian" package (subtle hint). Thanks to all for their advice in this matter. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html