An alternative method to predict performance: canonical redundancy analysis.

Abstract

The relationships between predictors of performance and subsequent measures of clinical performance in medical school were examined for two classes of students at Southern Illinois University School of Medicine. A relatively new statistical technique, canonical redundancy analysis, was used to evaluate the association between six academic and three biographical preselection characteristics and four measures clinical competence. While producing results consistent with the univariate methods traditionally used, the technique extends understanding of the total relationship between the two sets of measures. The preselection variable found to be most related to clinical competence was the undergraduate nonscience grade-point average. Overall, 16 percent of the variation in clinical performance was accounted for on the basis of knowledge of the preselection characteristics.