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A Necessary and Sufficient Condition for Identification of Confirmatory Factor Analysis Models of Factor Complexity One

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  • TERENCE REILLY

    (University of Oregon)

Abstract

After specification of a structural equation model and before estimation of parameters, the identification status of the model must be determined. For the measurement portion of the model, however, there are very few rules to help the researcher verify whether the model is identified or not. This article introduces a necessary and sufficient identification rule for models of factor complexity one. The rule is easy to understand, is easy to apply, and applies to portions as well as to the whole model. Moreover, it provides a diagnostic tool that helps with identification questions. Many examples are given.

Suggested Citation

  • Terence Reilly, 1995. "A Necessary and Sufficient Condition for Identification of Confirmatory Factor Analysis Models of Factor Complexity One," Sociological Methods & Research, , vol. 23(4), pages 421-441, May.
    • Handle: RePEc:sae:somere:v:23:y:1995:i:4:p:421-441
    DOI: 10.1177/0049124195023004002
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    References listed on IDEAS

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    1. Bekker, Paul A., 1989. "Identification in restricted factor models and the evaluation of rank conditions," Journal of Econometrics, Elsevier, vol. 41(1), pages 5-16, May.
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    Cited by:

    1. Benjamin Williams, 2018. "Identification of the Linear Factor Model," Working Papers 2018-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    2. Akshay Vij & Joan L. Walker, 2014. "Hybrid choice models: the identification problem," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 22, pages 519-564, Edward Elgar Publishing.

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