Stepwise Regression

Stepwise Regression is a model-building technique that finds subsets of predictor variables that most adequately predict responses on a dependent variable by linear (or nonlinear) regression, given the specified criteria for adequacy of model fit.

For an overview of stepwise regression and model fit criteria, see the Introductory Overview for General Regression Models (GRM) or the Overviews for Multiple Regression; for nonlinear stepwise and best subset regression, see Generalized Linear/Nonlinear Models (GLZ).