> -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] > project.org] On Behalf Of Frank E Harrell Jr > Sent: Saturday, September 27, 2008 7:15 PM > To: Darin Brooks > Cc: [EMAIL PROTECTED]; [EMAIL PROTECTED]; > [EMAIL PROTECTED] > Subject: Re: [R] FW: logistic regression > > Darin Brooks wrote: > > Glad you were amused. > > > > I assume that "booking this as a fortune" means that this was an > idiotic way > > to model the data? > > Dieter was nominating this for the "fortunes" package in R. (Thanks > Dieter) > > > > > MARS? Boosted Regression Trees? Any of these a better choice to > extract > > significant predictors (from a list of about 44) for a measured > dependent > > variable? > > Or use a data reduction method (principal components, variable > clustering, etc.) or redundancy analysis (to remove individual > predictors before examining associations with Y), or fit the full model > using penalized maximum likelihood estimation. lasso and lasso-like > methods are also worth pursuing.
Frank (and any others who want to share an opinion): What are your thoughts on model averaging as part of the above list? -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] 801.408.8111 ______________________________________________ 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.
