Missing Values with CHAID

Like the credit risk example (for more information, see Using Decision Trees to Evaluate Credit Risk), this example will try to build a model to classify good and bad credit risks. The main difference is that this data file contains missing values for some independent variables used in the model.
- To run a Decision Tree analysis, from the
menus choose:
Figure 2. Decision Tree dialog box - Select Credit rating as the dependent variable.
- Select all of the remaining variables as independent variables. (The procedure will automatically exclude any variables that don't make a significant contribution to the final model.)
- For the growing method, select CHAID.
For this example, we want to keep the tree fairly simple; so, we'll limit the tree growth by raising the minimum number of cases for the parent and child nodes.
- In the main Decision Tree dialog box, click Criteria.
Figure 3. Criteria dialog box, Growth Limits tab - For Minimum Number of Cases, type 400 for Parent Node and 200 for Child Node.
- Click Continue, and then click OK to run the procedure.