Vif Value In Regression Analysis. With Display VIF selected as an option Minitab will provide a table of coefficients as part of its output. Most research papers consider a VIF Variance Inflation Factor.
Computationally it is defined as the reciprocal of tolerance. Where R-squared is the coefficient of determination in linear regression. A general rule of thumb for interpreting VIFs is as follows.
The Variance Inflation Factor VIF is 1Tolerance it is always greater than or equal to 1.
If no factors are correlated the VIFs will all be 1. It makes the coefficient of a variable consistent but unreliable. You can interpret its reciprocal 1VIF as 1 - R2 where the R2 comes from the regression of that predictor on the other predictors. A VIF is a useful starting point but only a starting point.
