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Brennan, Jerry – Educational and Psychological Measurement, 1978
A computer program to compare factor matrices which have at least some variables in common is described. The program calculates both the salient variable similarity index and the congruence coefficient. There are no limits for the number of variables or factors in either matrix. (Author/JKS)
Descriptors: Comparative Analysis, Computer Programs, Factor Analysis, Matrices
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Kaiser, Henry F.; Dickman, Kern W. – Psychometrika, 1977
Three properties of the binormamin criterion for analytic transformation in factor analysis are discussed. Particular reference is made to Carroll's oblimin class of criteria. (Author)
Descriptors: Factor Analysis, Matrices, Oblique Rotation, Orthogonal Rotation
Peer reviewed Peer reviewed
Hubert, Lawrence J.; Baker, Frank B. – Journal of Educational Statistics, 1977
A statistical technique is proposed for comparing an empirically obtained matrix of the perceived similarity of paired stimuli against a set of distinctive features that supposedly characterize the stimuli on which the matrix is based. The statistical development of the technique and an example are presented. (Author/JKS)
Descriptors: Cues, Hypothesis Testing, Matrices, Nonparametric Statistics
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Collis, Glyn M. – Educational and Psychological Measurement, 1985
Some suggestions for measuring marginal symmetry in agreement matrices for categorical data are discussed, together with measures of item-by-item agreement conditional on marginal asymmetry. Connections with intraclass correlations for dichotomous data are noted. (Author)
Descriptors: Correlation, Interrater Reliability, Item Analysis, Matrices
Peer reviewed Peer reviewed
McQuitty, Louis L. – Educational and Psychological Measurement, 1983
Iterative Intercolumnar Correlation Classification (IICC) computes the correlation coefficients for the entries of every column of a matrix with those of every other column of the matrix. Iteration increases the size and validity of the object indices, reduces error in the indices, and increases homogeneity amongst them. (Author/BW)
Descriptors: Classification, Cluster Analysis, Correlation, Error Patterns
Peer reviewed Peer reviewed
Serlin, Ronald C.; Kaiser, Henry F. – Educational and Psychological Measurement, 1976
Internal consistency as one rationale for item selection from the unverse of possible test items is discussed and formulae are presented which relate the maximum internal consistency of a test to the largest eigenvalue of the interitem correlation matrix. A computer program to perform these calculations is presented. (Author/JKS)
Descriptors: Computer Programs, Item Sampling, Matrices, Test Construction
Morrisey, George L. – Personnel Administrator, 1976
The process of using paired comparisons in the Decision Matrix allows individuals involved in setting priorities to consider the pros and cons of each in reaching a rational decision about objective priorities. (Author/IRT)
Descriptors: Decision Making, Management by Objectives, Matrices, Objectives
Peer reviewed Peer reviewed
Hakstian, A. Ralph – Educational and Psychological Measurement, 1973
Formulas are presented in this paper for computing scores associated with factors of G, the image covariance matrix, under three conditions. The subject of the paper is restricted to "pure" image analysis. (Author/NE)
Descriptors: Factor Analysis, Matrices, Oblique Rotation, Statistical Analysis
Gillies, A. W. – Mathematical Gazette, 1971
Descriptors: Algebra, Instruction, Mathematics, Matrices
Peer reviewed Peer reviewed
Riccia, Giacomo Della; Shapiro, Alexander – Psychometrika, 1982
Some mathematical aspects of minimum trace factor analysis (MTFA) are discussed. The uniqueness of an optimal point of MTFA is proved, and necessary and sufficient conditions for any particular point to be optimal are given. The connection between MTFA and classical minimum rank factor analysis is discussed. (Author/JKS)
Descriptors: Data Analysis, Factor Analysis, Mathematical Models, Matrices
Peer reviewed Peer reviewed
Hubert, L. J.; Golledge, R. G. – Psychometrika, 1981
A recursive dynamic programing strategy for reorganizing the rows and columns of square proximity matrices is discussed. The strategy is used when the objective function measuring the adequacy of the reorganization has a fairly simple additive structure. (Author/JKS)
Descriptors: Computer Programs, Mathematical Models, Matrices, Statistical Analysis
Peer reviewed Peer reviewed
Olkin, Ingram – Psychometrika, 1981
It is known that for trivariate distributions, if two correlations are fixed, the remaining correlation is constrained. If just one is fixed, the remaining two are constrained. Both results are extended to the case of a multivariate distribution. (Author/JKS)
Descriptors: Correlation, Data Analysis, Matrices, Multiple Regression Analysis
Peer reviewed Peer reviewed
Tzeng, Oliver C. S.; May, William H. – Educational and Psychological Measurement, 1979
A strategy for reordering the hierarchical tree structure is presented. While the order of terminal nodes of Johnson's procedure is arbitrary, this procedure will rearrange every triad of nodes under a common least upper node so that the middle node is nonarbitrarily closest to the anchored node. (Author/CTM)
Descriptors: Cluster Analysis, Cluster Grouping, Matrices, Multidimensional Scaling
Rutt, David P. – Journal of Instructional Development, 1979
Presents a framework for examining the consulting relationship which includes four consultation models; and identifies and discusses two dimensions of the instructional developer's task environment that may influence the use of these models. Results and implications of a study using the framework are reported. (Author/JEG)
Descriptors: Consultants, Instructional Development, Matrices, Models
Peer reviewed Peer reviewed
Hubert, Lawrence J. – Psychometrika, 1979
Based on a simple nonparametric procedure for comparing two proximity matrices (matrices which represent the similarities among a set of objects), a measure of concordance (agreement) is introduced that is appropriate when K independent proximity matrices are available. (Author/JKS)
Descriptors: Matrices, Multidimensional Scaling, Nonparametric Statistics, Technical Reports
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