Hypotheses that do not have the standard bilinear form theta=CBM=0 occur naturally in the analysis of repeated measurement designs. An expanded class of the tests of the form psi=Tr(G theta)=0, called extended linear hypotheses, provides a richer class of parametric functions. A method to analyze double multivariate and mixed multivariate models…

A summary and a unified treatment of fully general computational solutions for two criteria for transforming two or more matrices to maximal agreement are provided. The two criteria--Maxdiff and Maxbet--have applications in the rotation of factor loading or configuration matrices to maximal agreement and the canonical correlation problem. (SLD)

The perturbation theory of the generalized eigenproblem is used to derive influence functions of each squared canonical correlation coefficient and the corresponding canonical vector pair. Three sample versions of these functions are described, and some properties are noted. Two obvious applications, multiple correlation and correspondence…

A new version of the standardized estimated parameter change that is invariant to the original metrics of the measured and latent variables is suggested for use in model modification. A multivariate estimated parameter change for a set of fixed parameters to be freed simultaneously is also introduced. (SLD)

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)

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)

The interpretation of discriminant functions as a follow-up to a significant multivariate analysis of variance is discussed. New indices are proposed that aid in identification and interpretation of the subset of response variables that contribute to a significant group discrimination. Their efficacy is compared to several commonly used…

The frequencies of "m" independent "p-way" contingency tables are analyzed by a model that assumes that the ordinal category data in each of "m" groups are generated from a latent continuous multivariate normal distribution. The model permits analysis of several groups of individuals simultaneously. (TJH)

Interpretations of relative variable importance in multivariate analysis of variance are discussed, with attention to (1) latent construct definition; (2) linear discriminant function scores; and (3) grouping variable effects. Two numerical ranking methods are proposed and compared by the bootstrap approach using two real data sets. (SLD)

A generalized measure of association and an associated test of significance are presented for nominal independent variables in which any number or combination of interval, ordinal, or nominal dependent variables can be analyzed. A permutation test of significance is provided for the new measure. (SLD)

Within the multivariate normality framework, a formula is provided for computation of the criterion-related validity of composite scores based on the highest (or lowest) of several equivalent measures. This partial composite score has more validity than each single observation, but less validity than a composite based on all observations. (SLD)

This paper proposes a generalization of Thurstonian probabilistic choice models for analyzing both multiple preference responses and their relationships. The approach is illustrated by modeling data from two multivariate preference experiments. Preliminary data analyses show that the extension can yield an adequate representation of multivariate…

Different ways that dependent variables can cause multivariate significance are illustrated. It is argued that univariate tests should not be used as follow-up procedures to identify the variables that can contribute to multivariate significance. Methods that can be used to determine the contributions individual variables make to multivariate…

The probability integral of the multivariate normal distribution (ND) has received considerable attention since W. F. Sheppard's (1900) and K. Pearson's (1901) seminal work on the bivariate ND. This paper evaluates the formula that represents the "n x n" correlation matrix of the "chi(sub i)" and the standardized multivariate…

L-scaling is introduced as a technique for determining the weights in weighted averages or scaled scores for T joint observations on K variables. The technique is so named because of its formal resemblance to the Leontief matrix of mathematical economics. L-scaling is compared to several widely-used procedures for data reduction, and the…