Logistic Regression with Nominal or Ordinal Responses
Fit Models for Categorical Responses
About Logistic Regression
For nominal response variables, the Fit Model platform fits a linear model to a multi-level logistic response function using maximum likelihood. Likelihood-ratio statistics and Lack of Fit tests are computed for the whole model. Likelihood-ratio tests and Wald tests can be computed for each effect in the model. When the response is binary, odds ratios (with confidence intervals) are available.
For ordinal response variables, the Fit Model platform fits the cumulative response probabilities to the logistic distribution function of a linear model using maximum likelihood. Likelihood-ratio test statistics are provided ...