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Peer reviewedAlexander, Ralph A.; And Others – Educational and Psychological Measurement, 1985
A comparison of measures of association for 2x2 data was carried out by computer analysis. For each of 1,539 tables, 14 measures of association were calculated and evaluated. A measure based on the odds-ratio (Chambers, 1982) was most accurate in capturing the rho underlying a majority of the tables. (Author/BW)
Descriptors: Computer Simulation, Correlation, Matrices, Research Methodology
Wager, Walter – Educational Technology, 1976
Develops a heuristic device called the Formative Evaluation Outcomes Matrix that systematizes the data from three commonly used formative evaluation instruments for the purpose of diagnosing faults in products of the design process. (Author)
Descriptors: Evaluation Methods, Formative Evaluation, Instructional Design, Matrices
Peer reviewedArpaia, Pasquale J. – Two-Year College Mathematics Journal, 1974
Descriptors: Algebra, College Mathematics, Mathematical Concepts, Mathematics Education
Peer reviewedten Berge, Jos M. F. – Educational and Psychological Measurement, 1973
A shortcut formula for the computation of "coefficients of invariance" in the comparison of factor structures is presented. A limitation of the coefficient of invariance is pointed out in the case of comparing two first principal components. (NE)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Peer reviewedShort, Edmund C. – Journal of Curriculum Studies, 1983
Shows how a matrix, developed for identifying various strategies of curriculum development, can provide a basis for making a policy analysis of alternative strategies. (RM)
Descriptors: Curriculum Development, Decision Making, Elementary Secondary Education, Matrices
Peer reviewedDong, Hei-Ki; Thomasson, Gary L. – Educational and Psychological Measurement, 1983
The triangular decomposition method is suggested as a general technique for obtaining the various measures of an ill-conditioned matrix. The advantages of using triangular decomposition are computing nicety, cost, and parsimony. (Author/PN)
Descriptors: Correlation, Matrices, Multivariate Analysis, Statistical Analysis
Peer reviewedde Leeuw, Jan – Psychometrika, 1982
Recent work (EJ 208 813) showing that generalized eigenvalue problems in which both matrices are singular can be solved by reducing them to similar problems of smaller order is discussed. Possible extensions of the work are indicated. (Author/JKS)
Descriptors: Mathematical Formulas, Matrices, Multivariate Analysis, Scaling
Peer reviewedFriedman, Sally; Weisberg, Herbert F. – Educational and Psychological Measurement, 1981
The first eigenvalue of a correlation matrix indicates the maximum amount of the variance of the variables which can be accounted for with a linear model by a single underlying factor. The first eigenvalue measures the primary cluster in the matrix, its number of variables and average correlation. (Author/RL)
Descriptors: Correlation, Mathematical Models, Matrices, Predictor Variables
Peer reviewedShapiro, Alexander – Psychometrika, 1982
The extent to which one can reduce the rank of a symmetric matrix by only changing its diagonal entries is discussed. Extension of this work to minimum trace factor analysis is presented. (Author/JKS)
Descriptors: Data Analysis, Factor Analysis, Mathematical Models, Matrices
Peer reviewedSteiger, James H. – Multivariate Behavioral Research, 1980
The goodness-of-fit of correlational pattern hypotheses has traditionally been assessed either with a likelihood ratio statistic or with a quadratic form statistic. Several alternative statistics, based on the use of the Fisher r-to-z transform, are proposed and assessed in a Monte Carlo experiment. (Author/JKS)
Descriptors: Correlation, Data Analysis, Hypothesis Testing, Longitudinal Studies
Peer reviewedAnd Others; Lissitz, Robert W. – Psychometrika, 1976
A generalization of the Procrustes problem (concerning solutions for least squares problems) in which the errors are weighted from the right, left, or both is provided. Mathematical derivations and an illustration are provided. (Author/JKS)
Descriptors: Least Squares Statistics, Mathematical Logic, Matrices, Statistical Analysis
Peer reviewedTrendafilov, Nickolay T. – Multivariate Behavioral Research, 1996
An iterative process is proposed for obtaining an orthogonal simple structure solution. At each iteration, a target matrix is constructed such that the relative contributions of the target majorize the original ones, factor by factor. The convergence of the procedure is proven, and the algorithm is illustrated. (SLD)
Descriptors: Algorithms, Factor Analysis, Factor Structure, Matrices
An Eigenvector Method for Estimating Item Parameters of the Dichotomous and Polytomous Rasch Models.
Peer reviewedGarner, Mary; Engelhard, George, Jr. – Journal of Applied Measurement, 2002
Describes a technique for obtaining item parameters of the Rasch model, a technique in which the item parameters are extracted from the eigenvectors of a matrix derived from comparisons between pairs of items. Describes advantages of this technique, which can be applied to both dichotomous and polytomous data. (SLD)
Descriptors: Estimation (Mathematics), Item Response Theory, Matrices, Test Items
Salisbury, David F. – Performance and Instruction, 1990
Describes basic concepts in the field of general systems theory (GST) and identifies commonalities that exist between GST and instructional systems design (ISD). Models and diagrams that depict system elements in ISD are presented, and two matrices that show how GST has been used in ISD literature are included. (11 references) (LRW)
Descriptors: Instructional Design, Literature Reviews, Matrices, Models
Peer reviewedMislevy, Robert J.; Sheehan, Kathleen M. – Journal of Educational Statistics, 1989
The structure of information matrices in latent-variable models is explicated, and the degree to which missing information can be recovered by exploring collateral variables for respondents is characterized. Results are illustrated in the context of item-response-theory models, and practical implications are discussed. (SLD)
Descriptors: Equations (Mathematics), Item Response Theory, Mathematical Models, Matrices


