# Can univariate linear regression be used to identify useful variables for a subsequent multiple logistic regression?

Does the $R^2$ (or some other statistic) from a univariate linear regression tell me anything about how it would work in a logistic model? What if I normalized the data to mean zero?

I'm doing multiple logistic regression, and I'm wondering if I created a ton of univariate linear regressions, if I can use the $R^2$ as an indicator of variables that are worth trying or not. Perhaps even adding a brute force search of interesting interactions or adding polynomials, etc.

• Normalising the data should not change $r^2$ – Henry Mar 2 '14 at 20:50
• this is the same as stepwise variable selection. see multiple posts on this topic elsewhere on this site – charles Mar 2 '14 at 21:59
• why not doing it on the logit model directly? You'll get a better assessment that way.. – user603 Mar 2 '14 at 22:00
• Thanks for your answers. The purpose of using Linear Regression was just to help with the computational complexity. ..I will read up on the backwards/forwards selection posts. – Jeremy Mar 2 '14 at 22:07