The purpose of this study was to determine which of six methods of ordering variables in a discriminant analysis yields subsets of variables that have the greatest discriminatory power. One method is based on univariate mean-square (or F) ratios, a second method on stepwise ordering, two methods on linear discriminant function (LDF) variable…

This study involved two phases: first when classification was based on the calibration sample, and second in a cross-validation setting. Computer-generated data were used. Results obtained from rules based on probabilities of group membership were compared for accuracy when classifying in the discriminant space and in the predictor variable…

Eight discriminators were identified and data were obtained from the records of 80 graduate students who attained one of four achievement levels at the conclusion of a beginning course in educational statistics. Although the internal discriminatory power of the set of eight measures was very high, estimates of the true power were discouragingly…

A linear classification rule (used with equal covariance matrices) was contrasted with a quadratic rule (used with unequal covariance matrices) for accuracy of internal and external classification. The comparisons were made for seven situations which resulted from combining three data conditions (equal and unequal covariance matrices, minimal and…

This study was concerned with various schemes for reducing the number of variables in a multivariate analysis. Two sets of illustrative data were used; the numbers of criterion groups were 3 and 5. The proportion of correct classifications was employed as an index of discriminatory power of each subset of variables selected. Of the four procedures…