Assessing Goodness of Fit: Simple Rules of Thumb Simply Do Not Work

• Published in: Organizational research methods Vol. 14; no. 3; pp. 548 - 570
• Main Authors: Nye, Christopher D., Drasgow, Fritz
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.07.2011; SAGE PUBLICATIONS, INC
• Subjects: Discriminant analysis; Empirical analysis; Estimating techniques; Goodness of fit; Least squares method; Mathematical analysis; Mathematical models; Maximum likelihood method; Organization theory; Regression; Simulation; Studies; fit indices; confirmatory factor analysis; model fit
• ISSN: 1094-4281; 1552-7425
• DOI: 10.1177/1094428110368562

Confirmatory factor analytic (CFA) models are frequently used in many areas of organizational research. Due to their popularity, CFA models and issues about their fit have received a vast amount of attention during the past several decades. The purpose of this study was to examine several measures of fit and the appropriateness of previously developed ‘‘rules of thumb’’ for their interpretation. First, an empirical example is used to illustrate the effects of nonnormality on maximum likelihood (ML) estimation and to demonstrate the importance of diagonally weighted least squares (DWLS) estimation for organizational research. Then, the results of a simulation study are presented to show that appropriate cutoff values for DWLS estimation vary considerably across conditions. Finally, regression equations are described to aid researchers in selecting cutoff values for assessing the fit of DWLS solutions, given a desired level of Type I error. The results summarized here have important implications for the interpretation and use of CFA models.