The variance inflation factor (VIF) is a measure used to detect multicollinearity in multiple linear regression models. It quantifies how much the variance of the estimated regression coefficients increases when your predictors are correlated. A high VIF indicates a high level of collinearity, which can distort the results of regression analysis and lead to unreliable conclusions.
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