Modeling and Multivariate Methods - SAS

152 Fitting Stepwise Regression Models Chapter 4
Using Validation
9. Click OK.
Figure 4.18 Model Averaging Report
In the Model Averaging report, average estimates and standard errors appear for each parameter. The
standard errors shown reflect the bias of the estimates toward zero.
10. Click Save Prediction Formula to save the prediction formula in the original data table.
Using Validation
Validation is the process of using part of a data set to estimate model parameters, and using the other part to
assess the predictive ability of the model.
• The training set is the part that estimates model parameters.
• The validation set is the part that assesses or validates the predictive ability of the model.
• The test set is a final, independent assessment of the model’s predictive ability. The test set is available
only when using a validation column.
The training, validation, and test sets are created by subsetting the original data into parts. Subsetting is
done through the use of a validation column on the Fit Model launch window.
The validation column’s values determine how the data is split, and what method is used for validation:
• If the column has two distinct values, then training and validation sets are created.
• If the column has three distinct values, then training, validation, and test sets are created.
• If the column has four or more distinct values, K-Fold cross validation is performed.
When you use validation, model fit statistics appear for the training, validation, and test sets.