Stepwise Discriminant Analysis Options in GDA
Select either Forward stepwise (effects can be entered or removed), Backward stepwise (effects can be removed or entered), Forward entry (effects can only be entered, and never be removed), or Backward removal (effects can only be removed, and once removed, never be re-entered into the model) as the Model building option on the Quick Specs dialog box - Advanced tab or the GDA Models Wizard--Extended Options - Advanced tab to display the following options. Use these options to steer the stepwise selection procedure; for a description of stepwise model building procedures, refer to the GDA Introductory Overview, as well as the General Regression Models (GRM) Introductory Overview.
| Element Name | Description |
|---|---|
| p1, enter, p2, remove | Select the p1, enter option button to guide the stepwise entry or removal of effects into or out of the model by the significance levels (p-values) specified in the p1, enter and p2, remove fields. In other words, an effect will be entered into the model if the statistical significance of its contribution to the prediction is better than (i.e., p less than) p1, enter; an effect will be removed from the model if the statistical significance of its contribution is worse than (i.e., p greater than) p2, remove. Thus, in Forward stepwise and Backward stepwise selection, where at each step effects can be entered into or removed from the model, p1, enter must be less than p2, remove, so that effects that are entered are not automatically removed in the next step, or vice versa. The p2, remove value is ignored when Forward entry is selected; the p1, enter value is ignored when Backward removal is selected. |
| F1 enter, F2 remove | Select the F1, enter option button to guide the stepwise entry or removal of continuous predictor variables into or out of the model by the F-values specified in the F1, enter and F2, remove fields. In other words, a predictor will be entered into the model if the F-value associated with the statistical significance of its contribution to the prediction is greater than F1, enter; a predictor will be removed from the model if the F-value associated with the statistical significance of its contribution is worse than F2, remove. Thus, in Forward stepwise and Backward stepwise selection, where at each step effects can be entered into or removed from the model, F1, enter must be greater than F2, remove, so that effects that are entered are not automatically removed in the next step, or vice versa. The F2, remove value is ignored when Forward entry is selected; the F1, enter value is ignored when Backward removal is selected. Note that these options are only available if only continuous predictors are in the model (i.e., no categorical predictors); this is because F-values for effects with different degrees of freedom (greater than 1) are not comparable, and hence, meaningful selections of effects can not be based on their comparison. |
| Max. steps | Enter the maximum number of steps that is to be performed in the stepwise selection of effects in the Max. steps field.
See also GDA - Index. |