Explanation:
A variance inflation factor (VIF) is used to detect multicollinearity (correlation between the independent variables) in regression analysis.
If a variable has a large VIF, it is highly correlated with the other variables in the model.
Variables with exceedingly high VIFs should be considered for exclusion from a model. Such a move tends to have little impact on the fitted values from the model.
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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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