Both predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA) require a decision to pool group covariance matrices, or alternatively, to retain separate group covariance matrices when the group covariance matrices are too dissimilar to pool. Pooling the group covariance matrices involves the so-called "linear"…

Each of the four classic multivariate analysis of variance (MANOVA) tests of statistical significance may lead a researcher to different decisions as to whether a null hypothesis should be rejected: (1) Wilks' lambda; (2) Lawley-Hotelling trace criterion; (3) Roy's greatest characteristic root criterion; and (4) Pillai's trace criterion. These…

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…

An international study was undertaken to determine the differences in attitude and approach to outdoor leadership preparation for experts from five nations. Characteristics derived from a canonical discriminant function analysis were used to explain the differences in North America and provide the foundation for a model program. (Author/CW)

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…