Hello Frank, Thank you for the extension and remarks. The basic weakness of stepwise regression VS going through all-subsets is very much agreed upon. Although from what I gather there is one case where all subsets will be a problem to implement, that is for very LARGE datasets - especially in the sense of a lot of explanatory variables, and also with regards to cases where we have more explanatory variables then data points. In such cases I wonder if using stepwise regression could be found to be more realistic to implement then all subsets checks. Then again, I imagine (although not from real experience) that shrinkage methods (used with LARS) could be practical in those cases too.
I am looking forward to meeting you on Tuesday and taking your first tutorial of the day, With regard, Tal On Sat, Jul 4, 2009 at 4:22 PM, Frank E Harrell Jr <f.harr...@vanderbilt.edu > wrote: > sed for one variable at a time variable selection. AIC is just a > restatement of the P-value, and as such, doesn't solve the severe problems > with stepwise v -- ---------------------------------------------- My contact information: Tal Galili Phone number: 972-50-3373767 FaceBook: Tal Galili My Blogs: http://www.r-statistics.com/ http://www.talgalili.com http://www.biostatistics.co.il [[alternative HTML version deleted]] ______________________________________________ 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.
