Ordinal Response Modeling with the LOGISTIC Procedure

Logistic regression is most often used for modeling simple binary response data. Two modifications extend it to ordinal responses that have more than two levels: using multiple response functions to model the ordered behavior, and considering whether covariates have common slopes across response functions. This paper describes how you can use the LOGISTIC procedure to model ordinal responses. Before SAS/STAT ® 12.1, you could use cumulative logit response functions with proportional odds. In SAS/STAT 12.1, you can fit partial proportional odds models to ordinal responses. This paper also discusses methods of determining which covariates have proportional odds. The reader is assumed to be familiar with using PROC LOGISTIC for binary logistic regression.