Sensitivity of fit indices to model misspecification and model types
Abbreviated Journal Title
Multivariate Behav. Res.
SEARCH; Mathematics, Interdisciplinary Applications; Social Sciences, ; Mathematical Methods; Psychology, Experimental; Statistics & Probability
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.
Multivariate Behavioral Research
"Sensitivity of fit indices to model misspecification and model types" (2007). Faculty Bibliography 2000s. 7111.