VIF > 5: High correlation, warranting investigation. It is calculated for each predictor variable in the model.
Mathematical Breakdown of the VIF Formula in Statistics
When predictors are highly correlated, the model struggles to estimate the coefficients accurately, leading to inflated standard errors. A common rule of thumb is as follows: VIF = 1: No correlation.
While there is no universal cutoff, many statisticians use specific thresholds to guide their decisions. Interpreting VIF Values Interpreting the magnitude of VIF is essential for diagnosing data issues.
Mathematical Breakdown of the VIF Formula
Mathematical Formula Mathematically, the VIF for a predictor \( X_i \) is expressed as: VIF i = 1 / (1 - R 2 i ) In this equation, \( R^2_i \) represents the R-squared value obtained from the regression of \( X_i \) on all other independent variables. This inflation results in lower t-statistics, which may cause statistically significant variables to appear insignificant.
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