What Strategies Can Be Used to Address Multicollinearity?
When multicollinearity is detected, several strategies can be used to address it. One approach is to remove one or more of the highly correlated variables from the model. Alternatively, combining variables into a single composite index can reduce multicollinearity. Regularization techniques, such as ridge regression or lasso regression, can also be employed to mitigate the effects of multicollinearity by adding a penalty term to the regression equation.
