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…

Multi-group discriminant analysis was used to identify the pre-enrollment demographic and academic factors that best separate the success classes in the first-year examinations of science students at the University of Benin. The predictor of success was performance in specialist subjects of the matriculation examination. (Author/MLW)

Making decisions about residential or day program placement for adults with developmental disabilities requires examination of multidimensional measures of behavior and thus the use of multivariate statistical techniques along with expert opinion. This study used adaptive and maladaptive cluster scores on the Inventory for Client and Agency…