Sensitivity of fit indices to model misspecification and model types

    Authors

    X. T. Fan;S. A. Sivo

    Comments

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    Abbreviated Journal Title

    Multivariate Behav. Res.

    Keywords

    SEARCH; Mathematics, Interdisciplinary Applications; Social Sciences, ; Mathematical Methods; Psychology, Experimental; Statistics & Probability

    Abstract

    The search for cut-off criteria of fit indices for model fit evaluation (e.g., Hu & Bentler, 1999) assumes that these fit indices are sensitive to model misspecification, but not to different types of models. If fit indices were sensitive to different types of models that are misspecified to the same degree, it would be very difficult to establish cut-off criteria that would be generally useful. The issue about SEM fit indices being sensitive to different types of models has not received sufficient attention, although there is some research suggesting that this might be the case (e.g., Kenny & McCoach, 2003). This study examines if fit indices are sensitive to different types of models while controlling for the severity of model misspecification. The findings show that most fit indices, including some very popular ones (e.g., RMSEA), may be sensitive to different types of models that have the same degree of specification error. The findings suggest that, for most fit indices, it would be difficult to establish cut-off criteria that would be generally useful in SEM applications.

    Journal Title

    Multivariate Behavioral Research

    Volume

    42

    Issue/Number

    3

    Publication Date

    1-1-2007

    Document Type

    Article

    Language

    English

    First Page

    509

    Last Page

    529

    WOS Identifier

    WOS:000250277700004

    ISSN

    0027-3171

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