Likelihood Ratio Tests

The likelihood ratio tests check the contribution of each effect to the model.

For each effect, the -2 log-likelihood is computed for the reduced model; that is, a model without the effect.
The chi-square statistic is the difference between the -2 log-likelihoods of the Reduced model from this table and the Final model reported in the model fitting information table.

If the significance of the test is small (less than 0.05) then the effect contributes to the model.

Some effects can be difficult to test. For example, the intercept cannot be tested in this model because removing the intercept simply causes one of the previously redundant factor levels to become non-redundant. See the topic Multinomial Logistic Regression Coefficients for more information.