Fitting Linear Models • Generalized Linear Models • Generalized Linear Model Fit Report • Whole Model Test
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Whole Model Test
The Whole Model Test table shows tests that compare the whole-model fit to the model that omits all the regression parameters except the intercept parameter. It also contains two goodness-of-fit statistics and the AICc value to assess model adequacy.
The Whole Model Test table shows these quantities:
Model
Lists the model labels.
Difference
The difference between the Full model and the Reduced model. This model is used to measure the significance of the regressors as a whole to the fit.
Full
The complete model that includes the intercepts and all effects.
Reduced
The model that includes only the intercept parameters.
–LogLikelihood
The negative log-likelihood for the respective models.
L-R ChiSquare
The likelihood ratio chi-square test statistic for the hypothesis that all regression parameters are zero. The test statistic is computed by taking twice the difference in negative log-likelihoods between the fitted model and the reduced model that has only an intercept.
DF
The degrees of freedom (DF) for the Difference between the Full and Reduced model.
Prob>ChiSq
The probability of obtaining a greater chi-square value by chance alone if the specified model fits no better than the model that includes only an intercept.
Goodness of Fit Statistic
Lists the two goodness-of-fit statistics: Pearson and Deviance.
ChiSquare
The chi-square test statistic for the respective goodness-of-fit statistics.
DF
The degrees of freedom for the respective goodness-of-fit statistics.
Prob>ChiSq
The p-value for the respective goodness-of-fit statistics.
Overdispersion
(Appears only when the Overdispersion Tests and Intervals option is selected in the launch window.) An estimate of the overdispersion parameter. See Statistical Details for the Generalized Linear Model Personality.
AICc
The corrected Akaike Information Criterion. For more information, see Likelihood, AICc, and BIC in Statistical Details.

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Help created on 10/11/2018