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Stopping stepwise: Why stepwise and similar selection methods are bad and what you should use

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Abstract

A common problem in regression analysis is that of variable selection. Often, you have a large number of potential independent variables, and wish to select among them, perhaps to create a 'best' model. One common method of dealing with this problem is some form of automated procedure, such as forward, backward, or stepwise selection. We show that these methods are not to be recommended, and present better alternatives using PROC GLMSELECT and other methods.

keywords: regression, selection, forward, backward, stepwise, glmselect

Online Materials

View the pdf for "Stopping stepwise".

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