Document 0842
 DOCN  M9650842
 TI    Application of multivariable optimal discriminant analysis in general
       internal medicine.
 DT    9605
 AU    Yarnold PR; Soltysik RC; McCormick WC; Burns R; Lin EH; Bush T; Martin
       GJ; Department of Medicine, Northwestern University Medical School,;
       Chicago, Illinois 60611, USA.
 SO    J Gen Intern Med. 1995 Nov;10(11):601-6. Unique Identifier : AIDSLINE
       MED/96162467
 AB    OBJECTIVE: To illustrate the use of multivariable optimal discriminant
       analysis (MultiODA). DESIGN: 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. MEASUREMENTS AND MAIN
       RESULTS: 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. CONCLUSIONS: 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 obtained
       (Study 4). These findings suggest that MultiODA has the potential to
       improve the accuracy of predictions made in general internal medicine
       research.
 DE    Acquired Immunodeficiency Syndrome/THERAPY  Comparative Study
       *Discriminant Analysis  Human  Internal Medicine/STATISTICS & NUMER DATA
       Logistic Models  Long-Term Care/*STATISTICS & NUMER DATA  *Multivariate
       Analysis  Patient Discharge/*STATISTICS & NUMER DATA  Patient
       Readmission/*STATISTICS & NUMER DATA  Patient Satisfaction/*STATISTICS &
       NUMER DATA  Research/*STATISTICS & NUMER DATA  Sensitivity and
       Specificity  Support, Non-U.S. Gov't  Support, U.S. Gov't, Non-P.H.S.
       Support, U.S. Gov't, P.H.S.  JOURNAL ARTICLE

       SOURCE: National Library of Medicine.  NOTICE: This material may be
       protected by Copyright Law (Title 17, U.S.Code).