Overdispersion

In models with binary response variables as in logistic regression, the default dispersion parameter (1.0) for the model may not be adequate. You can select the Overdispersion checkbox and then select either the Pearson or deviance option button as the estimate of the dispersion parameter.

If you specify deviance, the dispersion parameter is estimated by the deviance divided by its degrees of freedom. If you specify Pearson , the dispersion parameter is estimated by the Pearson statistic divided by its degrees of freedom. The adjustment is reflected in the scale parameter as it is proportional to the dispersion parameter.

Changing the overdispersion parameter affects the computational values of the parameter variances and covariances and the model likelihood, and all related statistics (for example, standard errors, prediction errors).