D. Wood and J. Erskine (1976) and B. Thompson (1989) provided bibliographies of roughly 130 applications of canonical correlation analysis, but the features of such reports have not been widely studied. This report examines the features of recent canonical reports, including substantive inquiries, but also measurement applications examining…

Simple modifications of principal component methods are described that have distinct advantages for structural analysis of relations among educational and psychological variables. The methods are contrasted theoretically and empirically with conventional principal component methods and with maximum likelihood factor analysis. (Author/GK)

Canonical correlation and redundancy analysis are two approaches to analyzing the interrelationships between two sets of measurements made on the same variables. A component method is presented which uses aspects of both approaches. An empirical example is also presented. (Author/JKS)

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)

An overview of several statistics useful in interpreting variates constructed by using canonical correlation analysis is presented. A computer program which calculates coefficients not typically provided by computer packages is discussed. An illustrative example of the output is provided. (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 review of the development of canonical correlation is presented and insufficiencies in applications from the literature are summarized. A list of analytical procedures for use in canonical correlation is detailed. The relationship between analysis and interpretation is emphasized. An example is presented. (JKS)

An Expectation-Maximization (EM) algorithm in a maximum likelihood framework is developed to estimate finite mixtures of multivariate regression and simultaneous equation models with multiple endogenous variables. A dataset with cross-sectional observations for a diverse sample of businesses illustrates the semiparametric approach. (SLD)

This article illustrates 2 follow-up procedures that can be used to examine multivariate analysis of variance (MANOVA) group differences: the univariate analysis of a linear composite variable and multivariate contrasts. A heuristic data set is used to demonstrate the procedures, and it is shown that the follow-up methods will not always yield…

Evaluates the efficacy of a multidimensional model of body image that incorporated the dimensions of perception, affect, cognition, and behavior. Results did not support the hypothesized four-factor model, but rather a model that consisted of three factors. The results highlight the multidimensionality of the body image construct and the…

A general model is developed for the analysis of multivariate multilevel data structures. Special cases of this model include: repeated measures designs; multiple matrix samples; multilevel latent variable models; multiple time series and variance and covariance component models. (Author)

Two Tukey multiple comparisons and Bonferroni and multivariate approaches are compared for their rates of Type I error and any-pairs power when multisample sphericity was not satisfied and the design was unbalanced. For tests of weighted means and for study conditions investigated, the Bonferroni procedure provides a workable solution. (TJH)

Univariate and multivariate corrections for range restriction were compared using scores of 147,288 Navy applicants on the Armed Services Vocational Aptitude Battery. Composite validities were corrected using the univariate and multivariate formulas. In general, multivariate corrections were more accurate than univariate corrections. This accuracy…

A method is presented for approximating the amount of bias in estimators with complex sampling distributions that are influenced by a variety of properties. The model is illustrated in the contexts of the bootstrap method and redundancy analysis. (SLD)

Mathematical relationships between three-mode component analysis and stationary component analysis are explored. Theorems are presented giving constraints that must be satisfied for equivalency between component representations provided by the methods. In general, the two approaches give mathematically distinct representations. (SLD)