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Variance Inflation Factor (VIF) quantifies the severity of multicollinearity in an ordinary least squares regression analysis. It provides an index that measures how much the variance (the square of the estimate's standard deviation) of an estimated regression coefficient is increased because of collinearity.

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Multicollinearity and Interaction Effects

I know similar questions were asked before. However, none of the existing answers help me with my problem: I have a gls model with y=B0+B1X1+B2X2+B3X1X2+e. The VIF value for X1 and the interaction eff …
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