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J. Intell. 2015, 3(1), 2-20; doi:10.3390/jintelligence3010002

Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

Department of Educational Psychology, Baylor University, One Bear Place #97301, Waco, TX 76798, USA
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Academic Editor: Paul De Boeck
Received: 13 November 2014 / Revised: 21 January 2015 / Accepted: 26 January 2015 / Published: 3 February 2015
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Abstract

Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds. View Full-Text
Keywords: confirmatory factor analysis; bi-factor model; Monte Carlo simulation confirmatory factor analysis; bi-factor model; Monte Carlo simulation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Morgan, G.B.; Hodge, K.J.; Wells, K.E.; Watkins, M.W. Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations. J. Intell. 2015, 3, 2-20.

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