Simulated data were employed to test the integrity of orthogonal factor solutions when varying sample size, factor pattern/structure coefficient magnitude, method of extraction (principal component vs. common factor), number of variables, number of factors, and degree of overextraction. Factor solutions’ integrity was operationalized by comparing sample factor/component patterns to known population factor patterns, from which measures of nonzero coefficient bias and variability, and zero coefficient bias and variability, were determined. Slopes of each of these measures across degrees of overextraction were determined and related to the experimental condition variables. Results showed that nonzero pattern/structure coefficients generally degrade with increased overextraction, with PCA coefficients exhibiting this property to a greater degree than CFA coefficients. With smaller sample size and small coefficient magnitude, the degradation was greater; with higher sample size and larger coefficients, coefficient degradation was usually not enough to yield incorrect factor/component structure interpretations.
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