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Peer reviewedRoskam, Edward E.; And Others – Multivariate Behavioral Research, 1992
First- and second-round commentaries on an article by L. Guttman are presented. The following authors responded, with two articles each: (1) E. E. Roskam and J. Ellis; (2) P. H. Schonemann; (3) A. R. Jensen; (4) J. C. Loehlin; and (5) J.-E. Gustafsson. (SLD)
Descriptors: Factor Analysis, Groups, Intelligence, Mathematical Models
Peer reviewedGuttman, Louis – Multivariate Behavioral Research, 1992
Argues that Jensen's article contains an inaccurate and misleading account of Spearman's work and distorts the basic concepts of factor analysis. The target article has failed in all its main objectives; its major failing is a result of the irrelevance of factor analysis to the study of group differences. (SLD)
Descriptors: Blacks, Equations (Mathematics), Factor Analysis, Groups
Peer reviewedNandakumar, Ratna; Stout, William – Journal of Educational Statistics, 1993
A detailed investigation is provided of Stout's statistical procedure (the computer program DIMTEST) for testing the hypothesis that an essentially unidimensional latent trait model fits observed binary item response data from a psychological test. Three refinements achieve greater power. The revised approach is validated using real data sets.…
Descriptors: Computer Simulation, Equations (Mathematics), Hypothesis Testing, Item Response Theory
Peer reviewedFrigon, Jean-Yves; Laurencelle, Louis – Educational and Psychological Measurement, 1993
The statistical power of analysis of covariance (ANCOVA) and its advantages over simple analysis of variance are examined in some experimental situations, and an algorithm is proposed for its proper application. In nonrandomized experiments, an ANCOVA is generally not a good approach. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Analysis of Variance, Educational Research


