Explanation:
The Variance Inflation Factor (VIF) is a metric used to quantify the severity of multicollinearity in an ordinary least squares regression analysis. It is calculated as , where is the R-squared from a regression of the explanatory variable on all other explanatory variables.
A high VIF indicates that the independent variable is highly collinear with the other independent variables in the model. This high correlation inflates the variance of the coefficient estimate, making it less reliable. Therefore, Option A is the correct implication.
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Q.75 What is the implication of a variable having a large variance inflation factor (VIF) in a model?
A
There is a high correlation between the variable and the other independent variables in the model.
B
The variables in the model are uncorrelated and thus appropriate in explaining the dependent variable.
C
There's a need to include more explanatory variables in the model.
D
Excluding the variable from the model would have a strong impact on the fitted values from the model.
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