When fit indices and residuals are incompatible.

Michael W. Browne, Robert C. MacCallum, Cheongtag Kim, Barbara L. Andersen, Ronald Glaser·2002·Psychological Methods

Abstract

Standard chi-square-based fit indices for factor analysis and related models have a little known property: They are more sensitive to misfit when unique variances are small than when they are large. Consequently, very small correlation residuals indicating excellent fit can be accompanied by indications of bad fit by the fit indices when unique variances are small. An empirical example of this incompatibility between residuals and fit indices is provided. For illustrative purposes, an artificial example is provided that yields exactly the same correlation residuals as the empirical example but has larger unique variances. For this example, the fit indices indicate excellent fit. A theoretical explanation for this phenomenon is provided using relationships between unique variances and eigenvalues of the fitted correlation matrix.

Cites (1)

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Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: When fit indices and residuals are incompatible. https://app.cochat.ai/papers/10.1037//1082-989x.7.4.403
The paper
Browne, M. W., MacCallum, R. C., Kim, C., Andersen, B. L., & Glaser, R. (2002). When fit indices and residuals are incompatible. Psychological Methods. https://doi.org/10.1037//1082-989x.7.4.403

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