Variable selection for multiple linear regression

There are different selection methods for multiple linear regression to test the predicting variables, in order to increase the efficiency of our analysis. Variable selection is a contested topic but in some cases it can be useful. I am going to take a review of four common methods (enter, forward selection, backward elimination, stepwise selection) and check the differences in the results with bootstrapping (number of incidences: 100). Continue reading “Variable selection for multiple linear regression”