Standard stepwise regression is a good way of identifying potential multicollinearity problems since we are able to see the impact on the model at each step that occurs when a

Standard stepwise regression is a good way of identifying potential multicollinearity problems since we are able to see the impact on the model at each step that occurs when a new variable is added to the model.For instance,if bringing in a new variable causes the sign to change on a previously entered variable,we have evidence of multicollinearity.


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