A measure of "clusterability" serves as the basis of a new methodology designed to preserve cluster structure in a reduced dimensional space. Similar to principal component analysis, which finds the direction of maximal variance in multivariate space, principal cluster axes find the direction of maximum clusterability in multivariate space.…

This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…

Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…

A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

The finite intersection test (FIT) developed by P. K. Krishnaiah (1964, 1965) is discussed and compared with more familiar methods for simultaneous inference. How the FIT can be used to analyze differences among all means for both univariate and multivariate experimental designs is explained. (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 theories of Kerlinger and Eysenck on the nature of the dimensions underlying social attitudes are discussed. Integrating principles from both theories, an alternative approach to the issue, is suggested and tested on the domain of attitudes toward education in relation to personality. (Author/JKS)

A Monte Carlo simulation study compared the power and Type I errors of the Wilks lambda statistic and the statistic of M. L. Puri and P. K. Sen (1971) on transformed data in a one-way multivariate analysis of variance. Preferred test procedures, based on robustness and power, are discussed. (SLD)

Investigates the equality of "p" correlated effect sizes for "k" independent studies in which treatment and control groups are compared using Hotelling's "T" statistic. Illustrates the procedure and discusses the importance of sample size. (SLD)

Across conditions, differences between population parameters defined by common factor analysis and component analysis are demonstrated. Implications for data analytic and theoretical issues related to choice of analytic model are discussed. Results suggest that principal components analysis should not be used to obtain parameters reflecting latent…

This article compares two methods for analyzing small sets of repeated measures data under normal and non-normal heteroscedastic conditions: a mixed model approach with the Kenward-Roger correction and a multivariate extension of the modified Brown-Forsythe (BF) test. These procedures differ in their assumptions about the covariance structure of…

The representation of multivariate data by icons is discussed. The factorial sun is suggested as superior to the commonly used snowflake or sun icons and as better representing the values of the different variables and their correlational structure. Two experiments with 60 college students demonstrate the factorial sun's superiority. (SLD)

Two recent indices of fit, the Relative Noncentrality Index (RNI) (R. P. McDonald and H. W. Marsh, 1990) and the Comparative Fit Index (P. M. Bentler, 1990), are shown to be algebraically equivalent in most applications, although one condition in which the RNI may be advantageous for model comparison is identified. (SLD)