All of the statistical tests in the Logistic Regression reports compare the fit of the specified model with subset or superset models, as illustrated in Figure 11.14. If a test shows significance, then the higher order model is justified.
• Whole model tests: if the specified model is significantly better than a reduced model without any effects except the intercepts.
• Lack of Fit tests: if a saturated model is significantly better than the specified model.
• Effect tests: if the specified model is significantly better than a model without a given effect.
Figure 11.14 Relationship of Statistical Tests