This example illustrates the specification for a stepwise multiple regression problem with categorical predictors. When categorical predictor variables or effects have more than a single degree of freedom, the stepwise and best-subset procedures in STATISTICA GLZ ensure that the coded (only sigma-restricted parameterization is allowed in stepwise and best subsets regression) variables representing the categorical predictors are moved in or out of the model as a block (so that always complete multi-degree of freedom effects are included or excluded from the final model).

Note that brief descriptive comments are enclosed in curly brackets. You can run this example with the example data file Exp.sta, Normal distribution and Identity link in the Startup Panel.

GLZ;

{ Dependent or response variable: }

{ Specification of grouping variables (factors); note that

{ Specification of continuous predictor variables (covariates) }

{ Here the bar operator is used to construct the full factorial

{ Forward stepwise regression is requested as the model building

{ The maximum number of steps is 10. }

{ p to enter is 0.10. }

{ p to remove is 0.10. }

For more examples, see GLZ Syntax Examples.