RE: Re: order of covariate inclusion

From: pbonate@ilexonc.com Subject: RE: [NMusers] Re: order of covariate inclusion Date: 9/25/2003 2:01 PM Leonid, I guess I think of forward stepwise modeling buidling more in terms of how I was taught to do it with linear regression. Like with SAS the most significant covariate (based on an F-test) is entered into the model first. If it is significant (based on SLENTRY) it stays in the model. Then the next most significant covariate is entered into the model. This process continues until all covariates are exhausted. Once a covariate is in the model it stays in the model. Again, I guess it depends on the correlations between covariates for whether something stays or goes into the model. Covariates that are uncorrelated should be unaffected by this method. So going back to your example. Suppose two covariates are highly correlated (age and weight). You test base + age base + weight. Both are significant. Then you test base + age + weight and one or both of them turn up as insignificant. What would you do? Thanks, pete