Choosing the Right Model

There are usually several models that pass the diagnostic checks, so you need tools to choose between them.

Automated Variable Selection. When constructing a model, you generally want to only include predictors that contribute significantly to the model. The Binary Logistic Regression procedure offers several methods for stepwise selection of the "best" predictors to include in the model.
Pseudo R-Squared Statistics. The r-squared statistic, which measures the variability in the dependent variable that is explained by a linear regression model, cannot be computed for logistic regression models. The pseudo r-squared statistics are designed to have similar properties to the true r-squared statistic.
Classification and Validation. Crosstabulating observed response categories with predicted categories helps you to determine how well the model identifies defaulters.