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Peer reviewedBieber, Stephen L.; Meredith, William – Psychometrika, 1986
Meredith's method of extracting a factorially invariant solution is adapted to longitudinal settings. An explorational estimation procedure is presented which attempts to identify the longitudinal factor components of an across occasion variance-covariance matrix. Data from 166 subjects on the Wechsler Adult Intelligence Scale is used to…
Descriptors: Factor Analysis, Factor Structure, Intelligence Tests, Longitudinal Studies
Peer reviewedRay, Michael L.; Heeler, Roger M. – Educational and Psychological Measurement, 1975
Methods for analyzing the multitrait-multimethod matrix are reviewed and the results of their application to a classic data set are compared. It is shown that different analysis methods can yield different validity conclusions, and that the results obtained are partly dependent on the subjective judgments of the users. (Author/RC)
Descriptors: Cluster Analysis, Comparative Analysis, Factor Analysis, Goodness of Fit
Peer reviewedAbbott, Robert D. – Educational and Psychological Measurement, 1975
Presents a series of analyses of Jackson's Personality Research Form items and scales to determine the apparent effects of the use of the differential validity index on more traditional item psychometric indices which have been used to reduce the confounding of trait scales and social desirability. (Author/RC)
Descriptors: Affective Measures, Factor Analysis, Item Analysis, Matrices
Skakun, Ernest N.; Hakstian, A. Ralph – 1974
Two population raw data matrices were constructed by computer simulation techniques. Each consisted of 10,000 subjects and 12 variables, and each was constructed according to an underlying factorial model consisting of four major common factors, eight minor common factors, and 12 unique factors. The computer simulation techniques were employed to…
Descriptors: Comparative Analysis, Factor Analysis, Least Squares Statistics, Matrices
Browne, Michael W. – 1973
This paper concerns situations in which a p x p covariance matrix is a function of an unknown q x 1 parameter vector y-sub-o. Notation is defined in the second section, and some algebraic results used in subsequent sections are given. Section 3 deals with asymptotic properties of generalized least squares (G.L.S.) estimators of y-sub-o. Section 4…
Descriptors: Analysis of Covariance, Factor Analysis, Matrices, Measurement Techniques
Curtis, Ervin W. – 1976
The optimum weighting of variables to predict a dependent-criterion variable is an important problem in nearly all of the social and natural sciences. Although the predominant method, multiple regression analysis (MR), yields optimum weights for the sample at hand, these weights are not generally optimum in the population from which the sample was…
Descriptors: Correlation, Error Patterns, Factor Analysis, Matrices
Peer reviewedMcQuitty, Louis L. – Educational and Psychological Measurement, 1976
A method of analysis is developed which accounts for whatever variance is present in the responses to test items, additive, configural or the two combined. The method is applied to successive column matrices which report frequencies or endorsements by categories of subjects to answer alternative sets of test items. Approaches are included which…
Descriptors: Analysis of Variance, Cluster Grouping, Factor Analysis, Individual Characteristics
Peer reviewedvan Driel, Otto P. – Psychometrika, 1978
In maximum likelihood factor analysis, there arises a situation whereby improper solutions occur. The causes of those improper solution are discussed and illustrated. (JKS)
Descriptors: Computer Programs, Data Analysis, Factor Analysis, Goodness of Fit
Peer reviewedJensen, Arthur R.; Weng, Li-Jen – Intelligence, 1994
The stability of psychometric "g," the general factor of intelligence, is investigated in simulated correlation matrices and in typical empirical data from a large battery of mental tests. "G" is robust and almost invariant across methods of analysis. A reasonable strategy for estimating "g" is suggested. (SLD)
Descriptors: Correlation, Estimation (Mathematics), Factor Analysis, Intelligence
Peer reviewedDeerwester, Scott; And Others – Journal of the American Society for Information Science, 1990
Describes a new method for automatic indexing and retrieval called latent semantic indexing (LSI). Problems with matching query words with document words in term-based information retrieval systems are discussed, semantic structure is examined, singular value decomposition (SVD) is explained, and the mathematics underlying the SVD model is…
Descriptors: Automatic Indexing, Documentation, Factor Analysis, Information Retrieval
Miyazaki, Yasuo; Frank, Kenneth A. – Journal of Educational and Behavioral Statistics, 2006
In this article the authors develop a model that employs a factor analysis structure at Level 2 of a two-level hierarchical linear model (HLM). The model (HLM2F) imposes a structure on a deficient rank Level 2 covariance matrix [tau], and facilitates estimation of a relatively large [tau] matrix. Maximum likelihood estimators are derived via the…
Descriptors: Methods, Factor Analysis, Computation, Causal Models
Hart, Kenneth R. – 1998
The purpose of this paper is to help higher education institutions determine how well their institutional effectiveness models match the North Central Association of Colleges and Schools Commission on Institutions of Higher Education Criterion Four requirements. The paper describes each of the major requirements as a domain in a matrix with…
Descriptors: Accreditation (Institutions), Accrediting Agencies, Factor Analysis, Higher Education
Peer reviewedGower, J. C. – Psychometrika, 1975
Concerned with another form of analysis of m sets of matrices, the Procrustes idea is generalized so that all m sets are simultaneously translated, rotated, reflected and scaled so that a goodness of fit criterion is optimised. A computational technique is given, results of which can be summarized in analysis of variance form. (RC)
Descriptors: Analysis of Variance, Data Analysis, Factor Analysis, Goodness of Fit
Hofman, Richard J. – 1975
In this paper 12 blind transformation procedures are applied to 18 data sets. The results of the analyses indicate that the orthotran transformation solution is not restricted to particular types of data as are so many other transformation solutions. The evidence presented in this paper strongly suggests that the orthotran solution must be…
Descriptors: Data Analysis, Factor Analysis, Factor Structure, Matrices
Reynolds, Thomas J. – 1976
A method of factor extraction specific to a binary matrix, illustrated here as a person-by-item response matrix, is presented. The extraction procedure, termed ERGO, differs from the more commonly implemented dimensionalizing techniques, factor analysis and multidimensional scaling, by taking into consideration item difficulty. Utilized in the…
Descriptors: Discriminant Analysis, Factor Analysis, Item Analysis, Matrices

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