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Implications of indeterminate factor-error covariances for factor construction, prediction, and determinacy

By Wim P. Krijnen


The assumptions of the model for factor analysis do not exclude a class of indeterminate covariances between factors and error variables (Grayson, 2003). The construction of all factors of the model for factor analysis is generalized to incorporate indeterminate factor-error covariances. A necessary and sufficient condition is given for indeterminate factor-error covariances to be arbitrarily small, for mean square convergence of the regression predictor of factor scores, and for the existence of a unique determinate factor and error variable. The determinate factor and error variable are uncorrelated and satisfy the defining assumptions of factor analysis. Several examples are given to illustrate the results

Topics: common factor analysis, confirmatory factor analysis, factor indeterminacy, factoranalyse, statistiek, Psychology (miscellaneous), No Hanze research focus area applicable, Science
Year: 2006
DOI identifier: 10.1007/s11336-004-1260-2
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Provided by: NARCIS
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