Outline the Variance Inflating Factor (VIF) and explain how it may be used to detect the...

Outline the Variance Inflating Factor (VIF) and explain how it may be used to detect the presence of multicollinearity.

Expert Solution

Variance inflation factor (VIF) is a measure of the amount of multicollinearity in a set of multiple regression variables. Mathematically, the VIF for a regression model variable is equal to the ratio of the overall model variance to the variance of a model that includes only that single independent variable. This ratio is calculated for each independent variable. A high VIF indicates that the associated independent variable is highly collinear with the other variables in the model.

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A variance inflation factor (VIF) provides a measure of multicollinearity among the independent variables in a multiple regression model.

Detecting multicollinearity is important because while it does not reduce the explanatory power of the model, it does reduce the statistical significance of the independent variables.

A large VIF on an independent variable indicates a highly collinear relationship to the other variables that should be considered or adjusted for in the structure of the model and selection of independent variable

Rahul Sunny answered 1 year ago

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