The onscreen output includes a row for each of parameter in the following table with a value for estimated value, standard error, z-score, p-value, and significance:
|Intercept||The value of the logit (Y) when all predictors are 0.|
|Predictors||A row for each predictor value (X1,X2,...,Xp).|
The following values are also output in the second column (estimate).
|Value||Description (appears in significance column)|
|ITERATIONS#||The number of Fisher Scoring iterations performed on the function.
With Step('true'), the function reports this number for each step.
|ROWS#||The number of rows of data received as input.|
|Residual deviance||The deviance, with degrees of freedom noted in the significance column.
Residual deviance is not displayed when the Family is GAMMA, NEGATIVE_BINOMIAL, or INVERSE_GAUSSIAN.
|Pearson goodness of fit||The sum of squared Pearson’s residual.|
|AIC||Akaike information criterion, a measure of the relative quality of the model for the given set of data.|
|BIC||Bayesian information criterion, partly based on the likelihood function and closely related to the AIC. BIC is a criterion for model selection among a finite set of models; the model with the lowest BIC is preferred.|
|Wald Test||Tests the goodness of fit.|
|Dispersion parameter||For GAUSSIAN, the value of this parameter is estimated from the data. For all other families, this parameter has the value 1.|
The coefficients are also stored in the table output_table for later use.