RE: Stepwise regression

From: "Piotrovskij, Vladimir [JanBe]" <VPIOTROV@janbe.jnj.com> Subject: RE: Stepwise regression Date: Mon, 11 Dec 2000 12:29:13 +0100 Thanks to all who responded on my posting about stepwise regression. Everybody agreed it is not the right way to build a covariate model, however, nobody suggested a universal solution. What is clear, we should not rely only on statistical significance and should always explore data before starting model building. Actually, graphical analysis should guide the model development. Suppose we have selected a structural model and fitted it to data. The next step can be plotting random effects (ETAs) versus available covariates and visual selection of a covariate which has the most significant impact on one of the PK parameters. Looking at the plots may also suggest a functional form of the relationship. Of course, the eye should be well trained... After fitting a model with the covariate included a new set of ETAs should be examined again. Log likelihood difference and AIC/BIC should be used to confirm the significance of the covariate, but not to guide model building. In case of highly correlated covariates like body size variables one have to choose the most practical one: body weight unless there are strong evidences that a derived variable like LBM or BSA can predict, say, CL much better. It should always be kept in mind that the goal of population PK modeling is to support treatment optimization: there is no need to include clinically irrelevant effects even if they are statistically significant at, say, alpha=0.95. Best regards, Vladimir