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Effect of estimation method on incremental fit indexes for covariance structure models
Sugawara, Hazuki M.; MacCallum, Robert C. (1993)
 

Title 
Effect of estimation method on incremental fit indexes for covariance structure models

Issue Date
1993

Type
Article

Abstract
In a typical study involving covariance structure modeling, fit of a model or a set of alternative models is evaluated using several indicators of fit under one estimation method, usually maximum likelihood. This study examined the stability across estimation methods of incremental and nonincremental fit measures that use the information about the fit of the most restricted (null) model as a reference point in assessing the fit of a more substantive model to the data. A set of alternative models for a large empirical dataset was analyzed by asymptotically distribution-free, generalized least squares, maximum likelihood, and ordinary least squares estimation methods. Four incremental and four nonincremental fit indexes were compared. Incremental indexes were quite unstable across estimation methods-maximum likelihood and ordinary least squares solutions indicated better fit of a given model than asymptotically distribution-free and generalized least squares solutions. The cause of this phenomenon is explained and illustrated, and implications and recommendations for practice are discussed. Index terms: covariance structure models, goodness of fit, incremental fit index, maximum likelihood estimation, parameter estimation, structural equation models.

Appears in Collection(s)

Other Identifier(s)
other: doi:10.1177/014662169301700405

Suggested Citation
Sugawara, Hazuki M.; MacCallum, Robert C.. (1993). Effect of estimation method on incremental fit indexes for covariance structure models. Retrieved from the University of Minnesota Digital Conservancy, http://purl.umn.edu/116375.


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