On Tue, 04 Dec 2001 17:39:53 GMT, Jerry Dallal <[EMAIL PROTECTED]> wrote:
> Rich Ulrich wrote: > > [ ... ] > > I don't see much difference. "Identifying predictors" by regression > > analyses -- what is that advice supposed to mean? The criticisms > > of stepwise selection say that it gives you the wrong variables, not > > 'merely' (as if that were trivial) the wrong weights. > > > > Am I missing something? (I am not totally against stepwise; > > just, mostly.) JD > > There are two issues: determining the right set of variables and > predicting the response. Stepwise can be deadly for the former > without, I believe, being too bad for the latter. I'm willing to > recant if someone with authority claims otherwise. I try to avoid the word "predict" when I am fitting parameters to describe a set of data or retrieve a formula - "post-dicting." That's okay, if that is what you mean. You are just talking about arriving at the minimum squared error in the fit. Oh, someone may ask, why not use them all? In my experience, I knew that there were supposed to be a certain number of variables in the equation; so I hoped to recover the actual formula, by restricting the variables. Starting out with pretty good hints as to variables and transformations, and some exact, tabled-up, results, I once used stepwise selection to recover a formula for the wind-chill index. Another time, I recovered the NFL formula for rating quarterbacks (and detected, with pretty high confidence, an error in the raw numbers). Right ballpark? -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================
