title: The identification of Class III malocclusions by discriminant analysis.
abstract: Lateral cephalometric radiographs of 210 control and 285 Class III subjects were traced, digitized, and 43 calculated variables submitted to a stepwise discriminant analysis. A 10-factor model was generated, giving 95.2 per cent correct classification of the control children and 95.1 per cent accurate identification of the Class III group. Ten control and 14 Class III children were categorized incorrectly. To test the validity of the analysis, radiographs of these 24 individuals were examined in detail. In all cases, a satisfactory reason for the misgrouping was identified. This investigation underlined the importance of rigorous standards of case selection when compiling the groups. The robustness of the 10-factor model was also examined. Subjects were arbitrarily split into two groups, the odd- and the even-numbered cases, and the discriminant analysis repeated on each. Both new models contained the same 10 variables, but with slightly different values for their accompanying coefficients. The cases erroneously identified by the whole group analysis were again misclassified, together with a few additional cases. Each new model performed equally well on the data from the opposing group as on that from which it had been derived. Thus, the model generated in this study was both valid and acceptably robust. It would therefore appear that discriminant analysis may be a viable tool in the identification and classification of groups of individuals.
authors.affiliation: Department of Child Dental Health, London Hospital Medical College Dental School.
authors.forename: J M
authors.initials: JM
authors.lastname: Battagel
mesh_terms: D000293:Adolescent; D000328:Adult; D016022:Case-Control Studies; D002508:Cephalometry / Q000379:methods* / Q000706:statistics & numerical data; D002648:Child; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D008297:Male; D008313:Malocclusion, Angle Class III / Q000175:diagnosis*; D008954:Models, Biological; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results