title: Quantified choice of root-mean-square errors of approximation for evaluation and power analysis of small differences between structural equation models.
abstract: MacCallum, Browne, and Cai (2006) proposed a new framework for evaluation and power analysis of small differences between nested structural equation models (SEMs). In their framework, the null and alternative hypotheses for testing a small difference in fit and its related power analyses were defined by some chosen root-mean-square error of approximation (RMSEA) pairs. In this article, we develop a new method that quantifies those chosen RMSEA pairs and allows a quantitative comparison of them. Our method proposes the use of single RMSEA values to replace the choice of RMSEA pairs for model comparison and power analysis, thus avoiding the differential meaning of the chosen RMSEA pairs inherent in the approach of MacCallum et al. (2006). With this choice, the conventional cutoff values in model overall evaluation can directly be transferred and applied to the evaluation and power analysis of model differences.
authors.affiliation: UCLA Integrated Substance Abuse Programs, 1640 South Sepulveda Boulevard, uite 200, Los Angeles, CA 90025, USA. lilibo@ucla.edu
authors.forename: Libo
authors.initials: L
authors.lastname: Li
authors.forename: Peter M
authors.initials: PM
authors.lastname: Bentler
mesh_terms: D006801:Humans; D008960:Models, Psychological; D015233:Models, Statistical; D011584:Psychology / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data*