Logistic multiple regression using the method of maximum likelihood is now the method of choice for many regression-type problems involving binary, ordinal. or nominal dependent variables. Logistic regression does not require grouping of observations to obtain valid estimates of effects and of outcome probabilities, and it has been shown in the binary case to provide more accurate probability e...

In contrast to the standard machine learning tasks of classification and metric regression we investigate the problem of predicting variables of ordinal scale, a setting referred to as ordinal regression. The task of ordinal regression arises frequently in the social sciences and in information retrieval where human preferences play a major role. Also many multi–class problems are really proble...

A survey on Mseleni joint disease in South Africa involved the scoring of pelvic X-rays of women to measure osteoporosis. The scores were ordinal by construction and ranged from 0 to 12. It is standard practice to use ordinary regression techniques with an ordinal response that has that many categories. We give evidence for these data that the constraints on the response result in a misleading ...

In contrast to the standard machine learning tasks of classi cation and metric regression we investigate the problem of predicting variables of ordinal scale, a setting referred to as ordinal regression. The task of ordinal regression arises frequently in the social sciences and in information retrieval where human preferences play a major role. Also many multi{class problems are really problem...

Nowadays the area under the receiver operating characteristics (ROC) curve, which corresponds to the Wilcoxon–Mann–Whitney test statistic, is increasingly used as a performance measure for binary classification systems. In this article we present a natural generalization of this concept for more than two ordered categories, a setting known as ordinal regression. Our extension of the Wilcoxon–Ma...

Ordinal regression analysis is a convenient tool for analyzing ordinal response variables in the presence of covariates. In this paper we extend this methodology to the case of continuous self-rating scales such as the Visual Analog Scale (VAS) used in pain assessment, or the Linear Analog Self-Assessment (LASA) scales in quality of life studies. These scales measure subjects' perception of an ...