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Skrondal, Anders – Multivariate Behavioral Research, 2000
Discusses the design and analysis of Monte Carlo experiments, with special reference to structural equation modeling. Outlines three fundamental challenges of Monte Carlo approaches and suggests some alternative procedures that challenge conventional wisdom. Asserts that comprehensive Monte Carlo studies can be done with a personal computer if the…
Descriptors: Monte Carlo Methods, Research Design, Research Methodology, Structural Equation Models
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Joachimsthaler, Erich A.; Stam, Antonie – Multivariate Behavioral Research, 1990
Mathematical programing formulas are introduced as new approaches to solve the classification problem in discriminant analysis. The research literature is reviewed, and an illustration using a real-world classification problem is provided. Issues relevant to potential uses of these formulations are discussed. (TJH)
Descriptors: Classification, Discriminant Analysis, Equations (Mathematics), Literature Reviews
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Widaman, Keith F. – Multivariate Behavioral Research, 1993
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…
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Factor Analysis
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Roskam, Edward E.; And Others – Multivariate Behavioral Research, 1992
First- and second-round commentaries on an article by L. Guttman are presented. The following authors responded, with two articles each: (1) E. E. Roskam and J. Ellis; (2) P. H. Schonemann; (3) A. R. Jensen; (4) J. C. Loehlin; and (5) J.-E. Gustafsson. (SLD)
Descriptors: Factor Analysis, Groups, Intelligence, Mathematical Models
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McDonald, Roderick P. – Multivariate Behavioral Research, 1979
Two major and two minor principles are shown to serve to generate a large number of multivariate models, including canonical analysis, factor analysis, and latent trait test theory. The statistical underpinnings of the theory are discussed. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Factor Analysis, Mathematical Models
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Child, Dennis – Multivariate Behavioral Research, 1984
The components of Cattell's motivational model are discussed. The Motivation and School Motivation Analysis Tests are described. While Cattell's model gives a valid structure of dynamic influences and methods of quantifying certain aspects of these influences, more refinement is needed before it can be applied effectively by classroom teachers.…
Descriptors: Attitude Measures, Classroom Environment, Educational Research, Elementary Secondary Education
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Guttman, Louis – Multivariate Behavioral Research, 1992
Argues that Jensen's article contains an inaccurate and misleading account of Spearman's work and distorts the basic concepts of factor analysis. The target article has failed in all its main objectives; its major failing is a result of the irrelevance of factor analysis to the study of group differences. (SLD)
Descriptors: Blacks, Equations (Mathematics), Factor Analysis, Groups
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Cronbach, Lee J. – Multivariate Behavioral Research, 1984
This article describes the evolution of Raymond B. Cattell's data box (covariation chart), a synoptic conception of psychological data, from its introduction in 1946. Analytical techniques and related methodologies developed from this model by Cattell and other psychological researchers are discussed. (BS)
Descriptors: Experimental Psychology, Factor Analysis, Longitudinal Studies, Models
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McArdle, J. Jack – Multivariate Behavioral Research, 1984
The many methodological contributions of Raymond B. Cattell to multivariate analysis are discussed in terms of contemporary issues in structural equation modeling. His factor analytic approach is compared with current modeling practices. A critical evaluation finds much of Cattell's work still innovative, technically advanced, and valuable to…
Descriptors: Analysis of Variance, Comparative Analysis, Estimation (Mathematics), Evaluation