Variance Inflation. Steps for Implementing VIF Run a multiple regression. First determine the coefficient of determination.
Variance inflation factors VIF measure how much the variance of the estimated regression coefficients are. May 09 2019 The most common way to detect multicollinearity is by using the variance inflation factor VIF which measures the correlation and strength of correlation between the predictor variables in a regression model. A general rule of thumb for interpreting VIFs is as follows.
Statisticians refer to this type of correlation as multicollinearity.
The value for VIF starts at 1 and has no upper limit. The variance inflation factor VIF quantifies the extent of correlation between one predictor and the other predictors in a model. Aug 06 2002 Variance inflation factors are one measure that can be used to detect multi-colinearity condition indices are another. A general rule of thumb for interpreting VIFs is as follows.
