In the Stepwise personality of the Fit Model platform, for models that include categorical variables, note the following information:
• When a regression model contains nominal or ordinal effects, those effects are represented by sets of indicator variables.
• When a categorical effect has only two levels, that effect is represented by a single indicator variable.
• When a categorical effect has k levels, where k > 2, then it must be represented by k-1 indicator variables.
In the Stepwise personality of the Fit Model platform, categorical variables (nominal and ordinal) are coded in a hierarchical fashion. This coding differs from coding in other least squares fitting platforms. In hierarchical coding, the levels of the categorical variable are successively split into groups of levels that most separate the means of the response. The splitting process achieves the goal of representing a k-level categorical variable by k - 1 terms.
Note: In hierarchical coding, the initial terms that are constructed represent the groups responsible for the greatest separation. The advantage of this coding scheme is that these informative terms have the potential to enter the model early.