Use backward elimination procedure to decide which predictor variables can be dropped from the regression model. Control the type I error at = . 10 at each stage
In using backward elimination procedure how to control for type I error?
In backward elimination, one variable gets dropped at each stage. This could lead to a type 1 error for a given α (say 0.05). How to calculate this error at each step? Please put details in the explanation.
I know how to calculate type I error in like a t-test setting, but I do not get how to apply the same concept to backward elimination.