David Reitter wrote: > What are the options to compare fits of logistic regression models? > > My models are fitted using 'glmmPQL' from the MASS and nlme > libraries. The models to be compared differ in their use of > covariates, e.g., > > model.1 <- glmmPQL(dep ~ pred1a * pred2, random=1|subj, family=binomial) > model.2 <- glmmPQL(dep ~ pred1b * pred2, random=1|subj, family=binomial) > > pred1a and pred1b are correlated, and I'd like to estimate their > relative predictive power. > > Both models use the same datasets, but the covariate structure is not > nested. > > ... > > Any comments would be appreciated - be it to clear up some > misconceptions on my part, or be it to solve my problem at hand.
Hi David, Two quick thoughts: 1) you can always use cross-validation. 2) I've recently become aware of the "Vuong test" (Vuong 1989, Econometrika): http://links.jstor.org/sici?sici=0012-9682(198903)57:2%3C307:LRTFMS%3E2.0.CO;2-J but I haven't had a chance to learn what it is. It might be useful. Would love to hear what you learn if you have a chance to look into it. Best Roger -- Roger Levy Email: [EMAIL PROTECTED] Assistant Professor Phone: 858-534-7219 Department of Linguistics Fax: 858-534-4789 UC San Diego Web: http://ling.ucsd.edu/~rlevy _______________________________________________ R-lang mailing list [email protected] http://pidgin.ucsd.edu/mailman/listinfo/r-lang
