A Mixed-Model Procedure for Analyzing Ordered Categorical Data

Abstract

A mixed-model procedure is developed for predicting the value of an ordered categorical response from knowledge of various predictor variables. This procedure resembles the best linear unbiased procedure of Henderson (1975, Biometrics 31, 423-447) for predicting the value of a quantitative response. The approach is based on a mixed-model version of the threshold model in which it is assumed that the observed category is determined by the value of an underlying unobservable continuous response that follows a mixed linear model. The results are illustrated by an application to the problem of predicting the degree of difficulty that will be experienced by a dairy cow in the birth of her calf.