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Peer reviewedLee, Howard B.; Comrey, Andrew L. – Multivariate Behavioral Research, 1978
Two proposed methods of factor analyzing a correlation matrix using only the off-diagonal elements are compared. The purpose of these methods is to avoid using the diagonal communality elements which are generally unknown and must be estimated. (Author/JKS)
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Matrices
Peer reviewedVasu, Ellen Storey – Educational and Psychological Measurement, 1978
The effects of the violation of the assumption of normality in the conditional distributions of the dependent variable, coupled with the condition of multicollinearity upon the outcome of testing the hypothesis that the regression coefficient equals zero, are investigated via a Monte Carlo study. (Author/JKS)
Descriptors: Correlation, Hypothesis Testing, Matrices, Monte Carlo Methods
Gardner, Martin – Scientific American, 1978
Presents mathematical games that involve a problem-solving matrix, multicolored cubes, and three-dimensional dominoes. The work of Alexander MacMahon is highlighted. (MA)
Descriptors: Games, Geometric Concepts, Mathematical Logic, Mathematical Models
Peer reviewedDobbins, Gregory; Strate, Gordon – American Mathematical Monthly, 1978
Matrix examples that have been used successfully in the classroom to illustrate group concepts are given along with observations made by students in working with them. (MN)
Descriptors: Algebra, College Mathematics, Higher Education, Instructional Materials
Peer reviewedHubert, Lawrence J.; Baker, Frank B. – Multivariate Behavioral Research, 1978
The strategy for investigating convergent and discriminant test validity, known as the multitrait-multimethod matrix, is investigated. A nonparametric significance testing procedure is suggested and demonstrated. (JKS)
Descriptors: Correlation, Hypothesis Testing, Mathematical Models, Matrices
Peer reviewedArabie, Phipps – Psychometrika, 1978
An examination is made concerning the utility and design of studies comparing nonmetric multidimensional scaling algorithms and their initial configurations, as well as the agreement between the results of such studies. Various practical details of nonmetric scaling are also considered. (Author/JKS)
Descriptors: Correlation, Goodness of Fit, Matrices, Monte Carlo Methods
Peer reviewedSpence, Ian; Young, Forrest W. – Psychometrika, 1978
Several nonmetric multidimensional scaling random ranking studies are discussed in response to the preceding article (TM 503 490). The choice of a starting configuration is discussed and the use of principal component analysis in obtaining such a configuration is recommended over a randomly chosen one. (JKS)
Descriptors: Correlation, Factor Analysis, Goodness of Fit, Matrices
Peer reviewedMcDonald, Roderick P. – Psychometrika, 1978
The relationship between the factor structure of a convariance matrix and the factor structure of a partial convariance matrix when one or more variables are partialled out of the original matrix is given in this brief note. (JKS)
Descriptors: Analysis of Covariance, Correlation, Factor Analysis, Factor Structure
Peer reviewedMcQuitty, Louis L.; Koch, Valerie L. – Educational and Psychological Measurement, 1976
A relatively reliable and valid hierarchy of clusters of objects is plotted from the highest column entries, exclusively, of a matrix of interassociations between the objects. Having developed out of a loose definition of types, the method isolates both loose and highly definitive types, and all those in between. (Author/RC)
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Data Analysis
Peer reviewedEaves, David – Journal of Multivariate Analysis, 1976
Vector sum of a white noise in an unknown hyperspace and an Ornstein-Uhlenbeck process in an unknown line is observed through sharp linear test functions over a finite time span. Parameters associated with white noise are determinable and index measure-equivalence classes in relevant sample space. Intraclass relative density provides a basis for…
Descriptors: Analysis of Covariance, Bayesian Statistics, Diffusion, Mathematical Models
Peer reviewedStowe, Randall W. – Educational and Psychological Measurement, 1985
The multitrait-multimethod matrix procedure was employed to examine the convergent and discriminant validity of the five subscales of the Career Maturity Inventory (CMI) Attitude Scale, Counseling Form B-1. (Author/LMO)
Descriptors: Attitude Measures, High Schools, Matrices, Multitrait Multimethod Techniques
Peer reviewedFormann, Anton K. – Psychometrika, 1986
It is shown that for equal parameters explicit formulas exist, facilitating the application of the Newton-Raphson procedure to estimate the parameters in the Rasch model and related models according to the conditional maximum likelihood principle. (Author/LMO)
Descriptors: Latent Trait Theory, Mathematical Models, Matrices, Maximum Likelihood Statistics
Peer reviewedNoma, Elliot; Olivastro, Dominic – Journal of the American Society for Information Science, 1985
A study comparing citations received by patents in given year to number received in subsequent years found that, even though influential patents remain influential, both highly and infrequently cited patents age at same rate. Distribution of patents by number of citations received is stable over time. (17 references) (EJS)
Descriptors: Citations (References), Comparative Analysis, Matrices, Models
Peer reviewedBell, John F. – Journal of Educational Statistics, 1985
This paper outlines the problems associated with the estimation of variance components in generalizability analyses using analysis of variance software, and discusses the most useful software currently available for this specialist application: the MIVQUE method of the Statistical Analysis System (SAS) procedure VARCOMP. (Author)
Descriptors: Analysis of Variance, Computer Software, Generalizability Theory, Matrices
Peer reviewedSchurr, K. Terry; Henriksen, L. W. – Educational and Psychological Measurement, 1984
Provided is a description of three methods for testing certain types of a priori hypotheses about differences among covariance matrices. Briefly outlined are procedures for using two computer programs, COFAMM and LISREL, for testing such hypotheses. Also provided are examples of application of the methods to a meaningful data set. (Author/BW)
Descriptors: Analysis of Covariance, Computer Software, Factor Analysis, Hypothesis Testing


