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Draper, John F. – 1974
A study was made of the problem of representing the expectations of mean squares associated with analysis of variance sources of variation for experimental designs. These designs have a factorial structure over repeated measures or, for some other reason, have variates within a factorial design not all of which are mutually independent. A simple…
Descriptors: Analysis of Variance, Expectation, Hypothesis Testing, Mathematical Models
Peer reviewedVelicer, Wayne F.; Fava, Joseph L. – Multivariate Behavioral Research, 1987
Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…
Descriptors: Analysis of Variance, Factor Analysis, Mathematical Models, Matrices
Betz, M. Austin – 1976
Simultaneous test procedures (STPS for short) in the context of the unrestricted full rank general linear multivariate model for population cell means are introduced and utilized to analyze interactions in factorial designs. By appropriate choice of an implying hypothesis, it is shown how to test overall main effects, interactions, simple main,…
Descriptors: Analysis of Variance, Hypothesis Testing, Interaction, Mathematical Models
Peer reviewedWilliams, John D. – Multiple Linear Regression Viewpoints, 1977
The problems of two way analysis of variance designs with unequal and disproportionate cell sizes are discussed. A variety of solutions are discussed and a new solution is presented. (JKS)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Matrices
Peer reviewedMarsh, Herbert W.; Hocevar, Dennis – Journal of Educational Measurement, 1983
This paper describes a variety of confirmatory factor analysis models that provide improved tests of multitrait-multimethod matrices, and compares three different approaches (the original Campbell-Fiske guidelines, an analysis of variance model, and confirmatory factor analysis models). (PN)
Descriptors: Analysis of Variance, Comparative Analysis, Evaluation Methods, Factor Analysis
Lunneborg, Clifford E. – 1980
The multiple regression or general linear model (GLM) is a parameter estimation and hypothesis testing model which encompasses and approaches the more familiar fixed effects analysis of variance (ANOVA). The transition from ANOVA to GLM is accomplished, roughly, by coding treatment level or group membership to produce a set of predictor or…
Descriptors: Analysis of Covariance, Analysis of Variance, Hypothesis Testing, Mathematical Models
Timm, Neil H. – 1977
Several procedures proposed in the literature for the analysis of growth curves are reviewed. Particular attention is given to the current issues in this area to guide practitioners in the selection of the most appropriate methodology. (Author)
Descriptors: Analysis of Covariance, Analysis of Variance, Hypothesis Testing, Mathematical Models
Peer reviewedCeurvorst, Robert W.; Krus, David J. – Applied Psychological Measurement, 1979
A method for computation of dominance relations and for construction of their corresponding hierarchical structures is presented. The link between dominance and variance allows integration of the mathematical theory of information with least squares statistical procedures without recourse to logarithmic transformations of the data. (Author/CTM)
Descriptors: Analysis of Variance, Information Theory, Least Squares Statistics, Mathematical Models
Peer reviewedSirotnik, Kenneth; Wellington, Roger – Journal of Educational Measurement, 1977
A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)
Descriptors: Analysis of Variance, Data Analysis, Item Sampling, Mathematical Models
PDF pending restorationWilliams, John D.; Wali, Mohan K.
A solution is proposed for analysis of variance procedures with missing cells, such as may occur when a control group is not assigned to any of the rows or columns of the various experimental groups. Mathematical models for two-way design are presented which define several variables; as well as row effect, column effect, and row and column…
Descriptors: Analysis of Variance, Control Groups, Experimental Groups, Hypothesis Testing
Noe, Michael J. – 1976
This study compared three approaches to the two-factor experiment with repeated measures on one factor: (1) the conventional mixed model analysis of variance, (2) the Greenhouse-Geisser conservative analysis of variance, and (3) multivariate extensions of analysis of variance. Computer simulated data were used in a total of 96 sets of covariance…
Descriptors: Analysis of Variance, Comparative Analysis, Computer Programs, Correlation
Timm, Neil H.; Carlson, James E. – Multivariate Behavioral Research Monographs, 1975
Simplicity and flexibility of the full rank linear model motivated this paper which introduces researchers to the theory necessary to understand the model and apply the theory in the analysis of some standard fixed effects experimental designs. The theory and examples should help researchers use the model as an experimental tool and a model for…
Descriptors: Analysis of Variance, Computer Programs, Geometry, Hypothesis Testing
Olson, George H. – 1975
The multivariate general linear hypothesis (MGLH) has received relatively little utilization in educational research and evaluation. This is surprising in view of the fact that recent publications have made the MGLH tractable by practitioners. This paper seeks to stimulate interest in the MGLH by reviewing recent applications, emphasizing the…
Descriptors: Analysis of Covariance, Analysis of Variance, Data Analysis, Educational Research
PDF pending restorationLarsson, Bernt – 1974
This report gives some simple examples of stability for one factor and 2 x 2 factorial analysis of variance, reliability and correlations. The findings are very different: from superstability (no transformation whatsoever can change the result) to almost total instability. This is followed by a discussion of applications to multivariate analysis,…
Descriptors: Analysis of Variance, Correlation, Discriminant Analysis, Factor Analysis


