Multinomial Logistic Regression Statistics

You can specify the following statistics for your Multinomial Logistic Regression:

Case processing summary. This table contains information about the specified categorical variables.

Model. Statistics for the overall model.

  • Pseudo R-square. Prints the Cox and Snell, Nagelkerke, and McFadden R 2 statistics.
  • Step summary. This table summarizes the effects entered or removed at each step in a stepwise method. It is not produced unless a stepwise model is specified in the Model dialog box.
  • Model fitting information. This table compares the fitted and intercept-only or null models.
  • Information criteria. This table prints Akaike’s information criterion (AIC) and Schwarz’s Bayesian information criterion (BIC).
  • Cell probabilities. Prints a table of the observed and expected frequencies (with residual) and proportions by covariate pattern and response category.
  • Classification table. Prints a table of the observed versus predicted responses.
  • Goodness of fit chi-square statistics. Prints Pearson and likelihood-ratio chi-square statistics. Statistics are computed for the covariate patterns determined by all factors and covariates or by a user-defined subset of the factors and covariates.
  • Monotinicity measures. Displays a table with information on the number of concordant pairs, discordant pairs, and tied pairs. The Somers' D, Goodman and Kruskal's Gamma, Kendall's tau-a, and Concordance Index C are also displayed in this table.

Parameters. Statistics related to the model parameters.

  • Estimates. Prints estimates of the model parameters, with a user-specified level of confidence.
  • Likelihood ratio test. Prints likelihood-ratio tests for the model partial effects. The test for the overall model is printed automatically.
  • Asymptotic correlations. Prints matrix of parameter estimate correlations.
  • Asymptotic covariances. Prints matrix of parameter estimate covariances.

Define Subpopulations. Allows you to select a subset of the factors and covariates in order to define the covariate patterns used by cell probabilities and the goodness-of-fit tests.

How to Select Statistics

This feature requires SPSS® Statistics Standard Edition or the Regression Option.

  1. From the menus choose:

    Analyze > Regression > Multinomial Logistic Regression...

  2. In the Multinomial Logistic Regression dialog box, click Statistics.
  3. Select the statistics you want.