# How to diagnose multicollinearity using the output of vif function in R?

I am running a logistic regression in R and am attempting to determine if multicollinearity is a problem with my model.
When I run vif() on my final model, I get GVIF and GVIF^1/(2*Df) columns. From what I have read GVIF^1/(2*Df) is what I should use to assess muticollinearity, but I have been unable to determine what values I should use as a cut-off point.

Any help would be greatly appreciated.

-
Before modelling, you should look at correlations between your (assumed) independent variables. I think you should rephrase your question to "how to identify multicolinearity" and ask on crossvalidated.com, instead. –  Brandon Bertelsen Oct 17 '12 at 17:27