The difference in statistical power between the original Bonferroni and five modified Bonferroni procedures that control the overall Type I error rate is examined in the context of a correlation matrix where multiple null hypotheses are tested. Power differences of less than 0.05 were typically observed for the modified Bonferroni procedures. (SLD)

A particular strategy for investigating effects resulting from a multivariate analysis of variance (MANOVA) is proposed. The strategy involves multiple two-group multivariate analyses. The two groups result from considering multivariate pairwise group contrasts or multivariate complex group contrasts. Assuming a given two-group analysis yields…

An alternative analysis of the two-group single response variable design is proposed. It involves the classification of experimental units to populations represented by the two groups. Three real data sets are provided to illustrate the utility of the classification analysis. A table of sample sizes required for the analysis is presented.…

The mathematical extension from scalars to matrices as a prerequisite for univariate to multivariate generalizations of statistical concepts and methods is discussed. One reason for several alternative techniques is the multitude of ways to generalize from univariate concepts to multivariate concepts. The additional complexity, and lack of…

The basic notion of variability is generalized from a univariate context to a multivariate context using two matrix functions, a determinant, and a trace, yielding a number of alternative multivariate indices of shared variation. Some problems in the interpretation of tests of multivariate hypotheses are reviewed. (Author/BW)

A method is presented for extending full versus restricted model testing to predictive discriminant analysis when the criterion of model accuracy is classification hit rate. An example is presented involving the dropout or school persistence of 76 5th graders, and a computer program for the analysis is introduced. (SLD)

An approach to statistical testing, which combines Neyman-Pearson hypothesis testing and Fisher significance testing, is recommended. The use of P-values in this approach is discussed in some detail. The author also discusses some problems which are often found in introductory statistics textbooks. The problems involve the definitions of…