A distinction is drawn between redundancy measurement and the measurement of multivariate association between two sets of variables. Several measures of multivariate association between two sets of variables are examined. (Author/JKS)

It is demonstrated that, in the presence of population information, a linear combination of true scores can be estimated more efficiently than by the same linear combination of the observed scores. Three criteria for optimality are discussed, but they yield the same solution, described as a multivariate shrinkage estimator. (Author/SLD)

Use of internal correlation for statistical analysis--as proposed by G. W. Joe and J. L. Mendoza (1989)--is discussed. Use of the bootstrap technique to deal with the distributional problem is questioned. Joe and Mendoza attempt the interpretation of the two linear composites that produce the largest internal correlation. (TJH)

The use of internal correlation for statistical analysis, as proposed by G. W. Joe and J. L. Mendoza (1989), is discussed. The suggestion of using bootstrapping is received well. Applications to collinearity are suggested. (TJH)

The source of an event-related brain potential (ERP) is estimated from multivariate measures of ERP on the head under several mathematical and physical constraints on the parameters of the source model. Statistical aspects of estimation are discussed, and new tests are proposed. (SLD)

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)

Examination of the stochastics of moderated multiple regression (MMR) reveals that MMR is an appropriate technique when predictors are fixed variables and the distribution of errors is normal but is not appropriate when predictors are random variables and the joint distribution of criterion and predictor variables is multivariate normal. (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)

Investigates the newsworthiness of international terrorism. Relates the concept of deviance as a predictor of newsworthiness to the specific attributes of terrorist events and their impact on media selection (coverage or no coverage) and prominence of coverage. (SR)

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…

A general model for two-level multivariate data, with responses possibly missing at random, is described. The model combines regressions on fixed explanatory variables with structured residual covariance matrices. The likelihood function is reduced to a form enabling computational methods for estimating the model to be devised. (Author)

Monte Carlo studies were conducted to compare four multivariate analysis of variance (MANOVA) simultaneous test procedures (STPs) in terms of power and Type I error under various conditions including violations of MANOVA assumptions. Results do not support the hypothesis that the moderately restricted STP is a good compromise between…

Type I error rates for the Johansen test were estimated using simulated data for a variety of conditions. Results indicate that Type I error rates for the Johansen test depend heavily on the number of groups and the ratio of the smallest sample size to the number of dependent variables. Sample size guidelines are presented. (SLD)

Lazraq and Cleroux (Psychometrika, 2002, 411-419) proposed a test for identifying the number of significant components in redundancy analysis. This test, however, is ill-conceived. A major problem is that it regards each redundancy component as if it were a single observed predictor variable, which cannot be justified except for the rare…