Running the analysis

  1. To run a Bayesian Loglinear Regression model analysis, from the menus choose: Analyze > Bayesian Statistics > Loglinear Models
    Figure 1. Bayesian Loglinear Regression Models dialog
    Bayesian Loglinear Regression Models dialog
  2. In the Bayesian Loglinear Regression Models dialog, select Gender [gender] as the Row variable and then select Employment Category [jobcat] as the Column variable.
  3. Select Estimate Bayes Factor as the Bayesian Analysis. The Estimate Bayes Factor option constitutes a natural ratio to compare the marginal likelihoods between a null and an alternative hypothesis.
  4. Click Criteria to specify analysis criteria for the Bayesian Log-Linear Regression model.
    Figure 2. Bayesian Loglinear Regression Models: Criteria dialog
    Bayesian Loglinear Regression Models: Criteria dialog
  5. Select the Ascending format option.
  6. Click Bayes Factor to specify the model that is assumed for the observed data.
    Figure 3. Bayesian Loglinear Regression Models: Bayes Factor dialog
    Bayesian Loglinear Regression Models: Bayes Factor dialog
    1. Select the Multinomial Model option. When selected, the Multinomial model is assumed for the observed data
    2. Select the Row Sum option under the Fixed Margins section to specify the fixed marginal totals for the contingency table.
    3. Select Mixture Dirichlet as the Prior Distribution method.
  7. Click Print to specify how the contents display in the output tables.
    Figure 4. Bayesian Loglinear Regression Models: Print dialog
    Bayesian Loglinear Regression Models: Print dialog
  8. Select the Chi-square and Likliehood ratio options under the Statistics section. The Chi-square option computes the Pearson Chi-Square statistic, degrees of freedom, and 2-sided asymptotic significance. The Likliehood ratio option computes the likelihood ratio test statistic, degrees of freedom, and associated 2-sided asymptotic significance.
  9. Click Run Analysis.

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