Regression, Discrimination and Measurement Models for Ordered Categorical Variables

Abstract

SUMMARY Regression models for the analysis of ordered categorical variables are discussed with particular reference to the logistic model. Maximum likelihood estimation procedures are established for three common sampling plans including the case where sampling is conditional on the ordered variable. This was previously not available. The use of these models in discrimination is discussed and an example given. An original method for the establishment of rating scales based on a coarse direct assessment and related variables is introduced. Mention is made of some difficulties in the application of the models and of their potential use for the analysis of designed experiments with ordered response variables.