COMPARISON OF DISCRIMINATION TECHNIQUES APPLIED TO A COMPLEX DATA SET OF HEAD INJURED PATIENTS

Several techniques for discriminant analysis are applied to a set of data from patients with severe head injuries, for the purpose of prognosis. The data are such that multidimensionality, continuous, binary and ordered categorical variables and missing data must be coped with. The various methods are compared using criteria of prognostic success and reliability. In general, performance varies more with choice of the set of predictor variables than with that of the discriminant rule.