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Peer reviewedMarsh, Herbert W.; Hocevar, Dennis – Journal of Educational Measurement, 1983
This paper describes a variety of confirmatory factor analysis models that provide improved tests of multitrait-multimethod matrices, and compares three different approaches (the original Campbell-Fiske guidelines, an analysis of variance model, and confirmatory factor analysis models). (PN)
Descriptors: Analysis of Variance, Comparative Analysis, Evaluation Methods, Factor Analysis
Peer reviewedMarsh, Herbert W. – Journal of Educational Measurement, 1987
This investigation tested the ability of an a priori hierarchical structure of self-concept derived from the Shavelson model to explain responses to the Self Description Questionnaire (SDQ) III, and demonstrated the application and problems with the use of hierarchical confirmatory factor analysis (HCFA). (Author/JAZ)
Descriptors: Factor Analysis, Factor Structure, Goodness of Fit, Mathematical Models
Peer reviewedZwick, Rebecca – Journal of Educational Measurement, 1987
National Assessment of Educational Progress reading data were scaled using a unidimensional item response theory model. Bock's full-information factor analysis and Rosenbaum's test of unidimensionality were applied. Conclusions about unidimensionality for balanced incomplete block spiralled data were the same as for complete data. (Author/GDC)
Descriptors: Factor Analysis, Item Analysis, Latent Trait Theory, Mathematical Models
Peer reviewedMuthen, Bengt O. – Journal of Educational Measurement, 1991
Data from the Second International Mathematics Study for 3,724 eighth graders are used to demonstrate the potential of multilevel factor analysis (MFA) methodology. Issues related to between-class and within-class decomposition of achievement variance and the change in this decomposition over the course of the eighth grade are revealed through…
Descriptors: Academic Achievement, Analysis of Variance, Classes (Groups of Students), Equations (Mathematics)


