The QUANTSELECT Procedure

The stepwise method is a modification of the forward selection technique in which effects already in the model do not necessarily stay there. You request this method by specifying SELECTION=STEPWISE in the MODEL statement.

In the implementation of the stepwise selection method, the same entry and removal approaches for the forward selection and backward elimination methods are used to assess contributions of effects as they are added to or removed from a model. Suppose you specify SELECT=SL. If, at a step of the stepwise method, any effect in the model is not significant at the level specified by the SLSTAY= method-option, then the least significant of these effects is removed from the model and the algorithm proceeds to the next step. This ensures that no effect can be added to a model while some effect currently in the model is not deemed significant. Only after all necessary deletions have been accomplished can another effect be added to the model. In this case, the effect whose addition yields the most significant statistic value is added to the model and the algorithm proceeds to the next step. The stepwise process ends when none of the effects outside the model is significant at the level specified by the SLENTRY= method-option and every effect in the model is significant at the level specified by the SLSTAY= method-option. In some cases, neither of these two conditions for stopping is met and the sequence of models cycles. In this case, the stepwise method terminates at the end of the second cycle.

Just as with forward selection and backward elimination, you can use the SELECT= method-option to change the criterion used to assess effect contributions. You can also use the STOP= method-option to specify a stopping criterion and use the CHOOSE= method-option to specify a criterion used to select among the sequence of models produced.