The rotation process can be very useful in discriminant analysis and multivariate analysis of variance. (CK)

Univariate procedures proposed by M. Brown and A. Forsythe (1974) and the multivariate procedures from D. Nel and C. van der Merwe (1986) were generalized to form five new multivariate alternatives to one-way multivariate analysis of variance (MANOVA) for use when dispersion matrices are heteroscedastic. These alternatives are evaluated for Type I…

An explicit statement of a statistic which is a nonparametric analog to one-way MANOVA is presented. The statistic is a multivariate extension of the nonparametric Kruskal-Wallis test (1952). In addition two post hoc procedures are developed and compared. (Author/JKS)

A convenient, two-stage general linear regression approach to analysis of variance is described for use in univariate or multivariate designs involving one repeated measurement factor and one or more independent classification factors. A brief illustrative example is provided. (Author)

A hypothesized data set is used to illustrate that canonical correlation analysis is a general linear model, subsuming other parametric procedures as special cases. Specific techniques included in analyses are t tests, Pearson correlation, multiple regression, analysis of variance, multivariate analysis of variance, and discriminant analysis. (SLD)

A small multivariate data set is used to illustrate the usefulness of structure coefficients when interpreting results of educational experiments. Data are analyzed using a multivariate analysis of variance (MANOVA), and results are interpreted in three different ways to determine the contribution of individual variables to prediction: (1) using…

The equivalence of one-way multivariate analysis of variance and canonical correlation is well known. The usefulness of canonical correlation analysis is performing factorial multivariate analysis of variance is demonstrated. (Author)

The Shine-Bower single subject ANOVA is extended to a multivariate case, with one example assuming between-variate dependencies among within-subject errors and the second assuming no between-variate dependencies among within-subject errors. Standard and simplified multivariate ANOVA procedures are used, respectively. (Author/CM)

The method of unweighted means (MUM) was studied to determine Type I error rates associated with various degrees of imbalance among the cell frequencies. Conditions under which the MUM is a reasonable alternative to the least squares method are discussed, and the issue of power is considered. (SLD)

Using a hypothetical data set of 24 cases concerning opinions on contemporary issues on which Democrats and Republicans might disagree, concrete examples are provided to illustrate that canonical correlation analysis is the most general linear model, subsuming other parametric procedures as special cases. Specific statistical techniques included…

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…

Multivariate analysis techniques employ various methods of optimally weighting variables to form composites. The interpretation of these composites in subsequent analyses is rarely straightforward, fraught with difficulties based upon the statistical properites of the estimated weights. This paper synthesizes interpretive guidelines for four…

The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)

In response to Webb and Shavelson (EJ 241 567), Nussbaum questions the relevance of the universe score variance as a meaning reliability index and whether it is useful to determine the weights which enter into a composite by means of maximum generalizability. (CM)

Answering Nussbaum's (TM 507 069) criticism, the generalizability coefficient for absolute decisions, the use of the error variance formula, composites of maximum generalizability, and covariance components are discussed as yardsticks of measurement precision with arguments for the use of each procedure to interpret data. (CM)