Which of the following statements about multicollinearity in multiple regression analysis is/are TRUE?
A) When multicollinearity exists, the computed statistical significance of regression coefficients might be incorrect.
B) One way to avoid multicollinearity is to use only one operational definition of any independent variable.
C) One way to deal with multicollinearity is to combine highly correlated independent variables into a single variable.
D) All of the above are true.

Question

Quizplus · Accepted Answer

A) When multicollinearity exists, it can create instability in the multiple regression model, leading to incorrect statistical significance of regression coefficients.
B) Using only one operational definition of any independent variable can reduce the chances of multicollinearity by eliminating the possibility of having multiple highly correlated variables.
C) Combining highly correlated independent variables into a single variable can also help to reduce multicollinearity. This can be done by creating a composite score or factor analysis to represent the shared variance among the correlated variables. Therefore, all options are true.

Which of the Following Statements About Multicollinearity in Multiple Regression