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Gabriel, Roy M. – 1975
Multidimensional scaling (MDS) a highly reliable measurement technique, often requires an overwhelming task of the subject in the data collection procedure. This investigation was designed to determine the loss of precision in solution associated with five degrees of systematic reduction in the data collection task. Data were simulated via Monte…
Descriptors: Data Analysis, Data Collection, Mathematical Models, Matrices
Hill, Richard K. – 1975
This study is an a priori demonstration of the applicability of multiple matrix sampling techniques to the practical research problem of parameter estimation. Three tests were administered to two separate but parallel populations, with one receiving item samples and the other receiving full tests. Special efforts were made to minimize the context…
Descriptors: Bias, Item Sampling, Matrices, Standardized Tests
Alvir, Howard P. – 1975
This four-part report discusses the planning of modules through the use of a matrix and contains two case studies as illustration. Part 1, "Applying the Matrix to an Existing Course Outline," shows how to analyze a course outline, adapt it to a matrix, and plan appropriate modules. Part 2, "Matrix Analysis," examines the matrix in order to…
Descriptors: Course Content, Curriculum Design, Educational Research, Higher Education
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
Timm, Neil H. – 1974
Multivariate models are demonstrated to analyze repeated measures profile and growth curve data when univariate or multivariate mixed model assumptions are not tenable. Standard mixed model tests are recovered from certain multivariate hypotheses. The procedures are illustrated using numerical examples. (Author/RC)
Descriptors: Hypothesis Testing, Matrices, Models, Nonparametric Statistics
Peer reviewedMeredith, William – Psychometrika, 1977
A group of factor analytic rotation procedures are developed which yield both hyperplane fittings and oblique Procrustean analyses as special cases. It is generally supposed that these techniques are rather different in approach. Illustrations are presented and discussed. (Author/JKS)
Descriptors: Factor Analysis, Mathematical Models, Matrices, Oblique Rotation
Peer reviewedMishisato, Shizuhiko – Psychometrika, 1984
This study formulates a property of a quantification method, the principle of equivalent partitioning. When used with Guttman's principle of internal consistency, the combination allows the analysis of correlational data in terms of the variate(s) chosen by the investigator. Applications to multiple-choice, rank-order, and paired comparison data…
Descriptors: Discriminant Analysis, Mathematical Models, Matrices, Multiple Choice Tests
Peer reviewedRubin, Donald B.; Thayer, Dorothy T. – Psychometrika, 1982
The details of EM algorithms for maximum likelihood factor analysis are presented for both the exploratory and confirmatory models. An example is presented to demonstrate potential problems in other approaches to maximum likelihood factor analysis. (Author/JKS)
Descriptors: Algorithms, Factor Analysis, Matrices, Maximum Likelihood Statistics
Peer reviewedDreger, Ralph Mason – Educational and Psychological Measurement, 1979
A program is described utilizing a microcomputer and tape drive with any contingency or chi-square table from 2x2 to 8x8. It requires only the entering of the number of rows and number of columns, plus one-time entry of cell frequencies. (Author/JKS)
Descriptors: Analysis of Variance, Computer Programs, Computers, Matrices
Peer reviewedKnapp, Thomas R. – Journal of Educational Statistics, 1979
This paper presents the generalized symmetric means approach to the estimation of population covariances, complete with derivations and examples. Particular attention is paid to the problem of missing data, which is handled very naturally in the incidence sampling framework. (CTM)
Descriptors: Analysis of Covariance, Matrices, Sampling, Statistical Analysis
Beretvas, S. Natasha; Furlow, Carolyn F. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Meta-analytic structural equation modeling (MA-SEM) is increasingly being used to assess model-fit for variables' interrelations synthesized across studies. MA-SEM researchers have analyzed synthesized correlation matrices using structural equation modeling (SEM) estimation that is designed for covariance matrices. This can produce incorrect…
Descriptors: Structural Equation Models, Matrices, Statistical Analysis, Synthesis
Peer reviewedStewart, Thomas R. – Multivariate Behavioral Research, 1974
Suggests a way of using factor analytic techniques to supplement multidimensional scaling in such a way as to provide a firm basis for evaluating multidimensional representations. (Author/RC)
Descriptors: Evaluation Criteria, Factor Analysis, Matrices, Multidimensional Scaling
Peer reviewedMcDonald, R. P. – Psychometrika, 1974
Maximum likelihood estimates of the free parameters, and an asymptotic likelihood-ratio test, are given for the hypothesis that one or more elements of a covariance matric are zero, and/or that two or more of its elements are equal. (Author/RC)
Descriptors: Analysis of Covariance, Computer Programs, Hypothesis Testing, Matrices
Peer reviewedLevin, Joseph – Multivariate Behavioral Research, 1974
Descriptors: Classification, Correlation, Factor Analysis, Mathematical Models
Peer reviewedGames, Paul A. – Educational and Psychological Measurement, 1975
Describes a set of five programs providing robust techniques that work well when the assumption of conventional analysis of variance have been violated. (Author/RC)
Descriptors: Analysis of Variance, Computer Programs, Matrices, Research Design

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