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Analysis of variances and covariances is misleading as a guide to a common factor model
Authors:Lloyd G. Humphreys  Randolph K. Park
Affiliation:University of Illinois, USA
Abstract:The “factor” analyses published by Schultz, Kaye, and Hoyer (1980) confused component and factor analysis and led in this case as in many others to unwarranted conclusions. They used component analysis to develop factor models that were subjected to restricted (confirmatory) maximum likelihood analysis, but the final models for which good fits with the observed correlations were obtained were not common factor models. They were, however, discussed as such and conclusions drawn accordingly. When their correlation matrices are analyzed by the principal factors method, two factors are sufficient to account for the intercorrelations. These two factors generally support the a priori expectation of a difference between intelligence tasks and spontaneous flexibility tasks. They are also quite similar in younger and older subjects, when similarity is judged in terms of factor pattern. Factor loadings for the younger subjects, however, are much smaller than expectations based on the respective ranges of talent in the two groups of subjects or on past experience with similar tests in undergraduate student populations.
Keywords:Requests for reprints should be sent to Lloyd G. Humphreys   425 Psychology Building   University of Illinois   Champaign   Illinois 61820   USA
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