12.3 IDENTIFYING MULTICOLLINEARITY USING VARIANCE INFLATION FACTORS
However, suppose we did not check for the presence of correlation among our predictors, and went ahead and performed the regression anyway. Is there some way that the regression results can warn us of the presence of multicollinearity? The answer is yes: We may ask for the variance inflation factors (VIFs) to be reported.
The VIF for the ith predictor is given by:
![equation](https://static.packt-cdn.com/products/9781119526810/graphics/images/c12-disp-0004.png)
where
A rough rule of thumb for interpreting the value of the VIF is to consider VIFi ≥ 5 to be an indicator of moderate multicollinearity, and to consider VIFi ≥ 10 to be an indicator of severe multicollinearity. A VIF of five corresponds to
For the regression of nutritional rating on fiber, potassium...