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Stepwise regression (often called forward or backward regression) involves fitting a regression model and adding or removing predictors based on $t$ statistics, $R^2$ or information criteria to arrive in a *stepwise* manner at a final model. This tag can also be used for forward selection, backward elimination & best subsets variable selection strategies.

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Does entry-order in stepwise regression matter even if there is no colinearity between predi...

I'm not sure I understand stepwise multiple regression, so I'll first try to share my understanding of it: We use several IV to predict one DV. In forward selection, we first enter the IV that increas …
Vilgot Huhn's user avatar