One in a series of nine articles in a section entitled, Electronic Computer Program and Accounting Machine Procedures."

Either linear or quadratic rules may be used to derive classification equations in discriminant analysis for the purpose of predicting group membership. Generally, the decision about which rule to use is governed by the degree to which the separate group covariance matrices are unequal. An example is presented that supports the superior internal…

Predictive discriminant analysis involves a technique used in multivariate classification, i.e., in predicting membership in well-defined groups for units on which multiple measures are available. The validation (assessment) of group membership predictions pertains to two problems: estimating true proportions of correct classifications (i.e., hit…

Three estimates of the probabilities of correct classification in predictive discriminant analysis were computed using mathematical formulas, resubstitution, and external analyses: (1) optimal hit rate; (2) actual hit rate; and (3) expected actual hit rate. Methods were compared using Monte Carlo sampling from two data sets. (Author/GDC)

The issues in the interpretation of discriminant analyses presented are restricted to the typical uses of discriminant analysis by behavioral science researchers. Because behavioral researchers use computer programs packages, the issues discussed deal with information obtainable from the package discriminant analysis programs. The following issues…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Linear classification functions (LCFs) arise in a predictive discriminant analysis for the purpose of classifying experimental units into criterion groups. The relative contribution of the response variables to classification accuracy may be based on LCF-variable correlations for each group. It is proved that, if the raw response measures are…