RE: Bootstrap resampling!

From: "Gibiansky, Leonid" <gibianskyl@globomax.com> Subject: RE: Bootstrap resampling! Date: Thu, 29 Mar 2001 07:52:33 -0500 There was one more use of the bootstrap procedure (that I've learned from Lewis Sheiner talk) that was not mentioned in this discussion (or mentioned very briefly). It was proposed for investigation of the covariate model. The idea was to disassociate patients and their covariates. For example, when you study importance of gender, you take patients with all their history (concentrations, dosing, all the other covariates except gender) and randomly bootstrap gender covariate for each patient from the "observed" set of gender variable for the population under study. Then you fit the model with gender covariate and without it and see how often gender appears to be significant. It is clear that for the bootstrap sample constructed in this manner the gender is random and should not be significant. Then the number of false-positive results can be used to characterize the significance of the covariate and see how often it appears to be significant just by chance. I have not tried the procedure but found it a very elegant although time-consuming way to investigate the covariate model especially for the small data sets. Is there anybody in the group who tried this approach ? If yes, could you describe your experience ? Thanks, Leonid Gibiansky