PMID: 8583262Nov 1, 1995Paper

Application of multivariable optimal discriminant analysis in general internal medicine

Journal of General Internal Medicine
P R YarnoldG J Martin

Abstract

To illustrate the use of multivariable optimal discriminant analysis (MultiODA). Data from four previously published studies were reanalyzed using MultiODA. The original analysis was Fisher's linear discriminant analysis (FLDA) for two studies and logistic regression analysis (LRA) for two studies. In Study 1, FLDA achieved an overall percentage accuracy in classification (PAC) for the training sample of 69.9%, compared with 73.5% for MultiODA. In Study 2, the LRA model required three attributes to achieve a 76.1% overall PAC for the training sample and a 79.4% overall PAC for the hold-out sample. Using only two attributes, the MultiODA model achieved similar values. In Study 3, the FLDA model achieved an overall PAC of 82.5%, compared with 87.5% for the MultiODA model. In Study 4, MultiODA identified a two-attribute model that achieved a 93.3% overall training PAC, when an LRA model could not be developed. MultiODA identified: a superior training model (Study 1); a more parsimonious model that achieved superior overall training and identical hold-out PAC (Study 2); a model that achieved a higher hold-out PAC (Study 3); and a two-attribute model that achieved a relatively high PAC when a multivariable LRA model could not be obt...Continue Reading

References

Sep 1, 1991·Journal of General Internal Medicine·R Burns, L O Nichols
Nov 1, 1991·Journal of General Internal Medicine·W C McCormickR W Wood
Jan 1, 1991·Journal of General Internal Medicine·W C McCormickR W Wood
Oct 1, 1993·Perceptual and Motor Skills·P R YarnoldS D Nightingale
Oct 1, 1990·Multivariate Behavioral Research·E A Joachimsthaler, A Stam

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Citations

Mar 31, 2005·Journal of the American College of Nutrition·Eun Ju YangWon O Song
Dec 12, 2003·The American Journal of Clinical Nutrition·Jean M KerverWon O Song

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