Interpreting Alias table testing multicollinearity of model in R

Question

Could someone help me interpret the alias function output for testing for multicollinearity in a multiple regression model. I know some predictor variables in my model are highl

Answer 1

Nonzero entries in the "complete" matrix show that those terms are linearly dependent on UseMonthly. This means they're highly correlated, but terms can be highly correlated without being linearly dependent.

If your purpose is to identify and remove correlated variables, you should remove UseMonthly, but you'll probably also want to remove others as well. A common way to identify variables which can be problematic with respect to multicollinearity is to search for large variance inflation factors (calculated by e.g. car::vif).