Variance Inflation Factor Regression. VIF measures the number of inflated variances caused by multicollinearity. Variance Inflation Factors VIFs measure the correlation among independent variables in least squares regression models.
We say that our model has problems with multicollinearity if. The Variance Inflation Factor VIF is 1Tolerance it is always greater than or equal to 1. It is calculated by taking the the ratio of the variance of all a given models betas divide by the variane of a single beta if it were fit alone.
As a rule of thumb a variable whose VIF values are greater than 10 may merit further investigation.
Multicollinearity can arise from poorly designed experiments Data-based multicollinearity or from creating new independent variables related to the existing ones structural multicollinearity. It is calculated by taking the the ratio of the variance of all a given models betas divide by the variane of a single beta if it were fit alone. The Variance Inflation Factor VIF measures the impact of collinearity among the variables in a regression model. The Variance Inflation Factor VIF is a measure of colinearity among predictor variables within a multiple regression.
