Dear All, For logistic regression models: is it possible to use validate (rms package) to compute bias-corrected AUC, but have variable selection with AIC use step (or stepAIC, from MASS), instead of fastbw?
More details: I've been using the validate function (in the rms package, by Frank Harrell) to obtain, among other things, bootstrap bias-corrected estimates of the AUC, when variable selection is carried out (using AIC as criterion). validate calls predab.resample, which in turn calls fastbw (from the Design package, by Harrell). fastbw " Performs a slightly inefficient but numerically stable version of fast backward elimination on factors, using a method based on Lawless and Singhal (1978). This method uses the fitted complete model (...)". However, I am finding that the models returned by fastbw are much smaller than those returned by stepAIC or step (a simple example is shown below), probably because of the approximation and using the complete model. I'd like to use step instead of fastbw. I think this can be done by hacking predab.resample in a couple of places but I am wondering if this is a bad idea (why?) or if I am reinventing the wheel. Best, R. P.S. Simple example of fastbw compared to step: library(MASS) ## for stepAIC and bwt data example(birthwt) library(rms) bwt.glm <- glm(low ~ ., family = binomial, data = bwt) bwt.lrm <- lrm(low ~ ., data = bwt) step(bwt.glm) ## same as stepAIC(bwt.glm) fastbw(bwt.lrm) -- Ramon Diaz-Uriarte Structural Biology and Biocomputing Programme Spanish National Cancer Centre (CNIO) http://ligarto.org/rdiaz Phone: +34-91-732-8000 ext. 3019 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
