Methods of ordinal classification applied to medical scoring systems.

Scoring systems are used in nearly all fields of medicine for evaluation of the state of a disease. The prediction performance of scoring systems with respect to an ordinal outcome scale is investigated, based on grouped continuous logistic models as well as on an extension of the stereotype logistic regression model. The latter is a canonical approach, which allows assessment of properties of outcome categories such as partial and total ordering, distinguishability and allocatability. The approach is applied to a data set of patients with injuries of the head.