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The Analysis of Covariance Structures

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  • JON W. HOELTER

    (University of Cincinnati)

Abstract

A major problem encountered in covariance structure analyses involves decisions concerning whether or not a given theoretical model adequately represents the data used for its assessment. Given that X 2 goodness-of-fit tests are joint functions of the difference between theoretical and empirical covariance structures and sample size, gauging the impact of sample size on such tests is essential. In this paper, we propose a simple index (critical N) and tentative acceptance criterion, which, by focusing on sample size, provide an improved method for assessing goodness-of-fit. Both small- and large-sample examples are presented, illustrating the utility of the proposed method for assessing theoretical models.

Suggested Citation

  • Jon W. Hoelter, 1983. "The Analysis of Covariance Structures," Sociological Methods & Research, , vol. 11(3), pages 325-344, February.
    • Handle: RePEc:sae:somere:v:11:y:1983:i:3:p:325-344
    DOI: 10.1177/0049124183011003003
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    References listed on IDEAS

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    1. E. Fuller & W. Hemmerle, 1966. "Robustness of the maximum-likelihood estimation procedure in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(2), pages 255-266, June.
    2. Ledyard Tucker & Charles Lewis, 1973. "A reliability coefficient for maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 38(1), pages 1-10, March.
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    1. Grissemann, Ursula S. & Stokburger-Sauer, Nicola E., 2012. "Customer co-creation of travel services: The role of company support and customer satisfaction with the co-creation performance," Tourism Management, Elsevier, vol. 33(6), pages 1483-1492.

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