RE: order of covariate inclusion -> avoiding stepwise a pproaches -> abandoning exploratory analysis?

From: chuanpu.2.hu@gsk.com Subject: RE: [NMusers] order of covariate inclusion -> avoiding stepwise a pproaches -> abandoning exploratory analysis? Date: 9/26/2003 9:36 AM Marc, I enjoyed reading your posts. Stepwise procedure, as a specific case of model exploration, has awful properties in statistical inference. For this reason, I advocated restricting model explorations, in a scenario where the inference properties are important, at the last PAGE meeting ( http://www.page-meeting.org/page/page2003/Chuanpu.pdf). The essence is that model exploration increases the chance of finding the "right" model (by that I mean "better", I should say), but also making the inference properties worse, hence there is a balance that needs to be maintained. The optimal balance may depend on your goal of the modeling exercise. One particular type of practical challenge comes from estimating a large model that the data could not quite support. As you suggested, one frequently has to make compromises in actual applications. A note: the term you used "not statistics" could be terribly misunderstood. (I think you mean something like "not stepwise regression.") To produce credible results, our procedures must have sound statistical properties, which includes correct standard errors, type I errors, etc. Best regards, Chuanpu -------------------------------------------------------------------------- Chuanpu Hu, Ph.D. Research Modeling and Simulation Clinical Pharmacology Discovery Medicine GlaxoSmithKline P.O. Box 13398 Five Moore Drive Research Triangle Park, NC 27709 Tel: 919-483-8205 Fax: 919-483-6380