title: Detecting Misspecified Multilevel Structural Equation Models with Common Fit Indices: A Monte Carlo Study.
abstract: This study investigated the sensitivity of common fit indices (i.e., RMSEA, CFI, TLI, SRMR-W, and SRMR-B) for detecting misspecified multilevel SEMs. The design factors for the Monte Carlo study were numbers of groups in between-group models (100, 150, and 300), group size (10, 20, 30, and 60), intra-class correlation (low, medium, and high), and the types of model misspecification (Simple and Complex). The simulation results showed that CFI, TLI, and RMSEA could only identify the misspecification in the within-group model. Additionally, CFI, TLI, and RMSEA were more sensitive to misspecification in pattern coefficients while SRMR-W was more sensitive to misspecification in factor covariance. Moreover, TLI outperformed both CFI and RMSEA in terms of the hit rates of detecting the within-group misspecification in factor covariance. On the other hand, SRMR-B was the only fit index sensitive to misspecification in the between-group model and more sensitive to misspecification in factor covariance than misspecification in pattern coefficients. Finally, we found that the influence of ICC on the performance of targeted fit indices was trivial.
authors.affiliation: a Department of Leadership and Counselor Education , University of Mississippi.
authors.forename: Hsien-Yuan
authors.initials: HY
authors.lastname: Hsu
authors.affiliation: b Department of Educational Psychology , Texas A&M University.
authors.forename: Oi-Man
authors.initials: OM
authors.lastname: Kwok
authors.affiliation: c Institute of Education , National Chiao Tung University.
authors.forename: Jr Hung
authors.initials: JH
authors.lastname: Lin
authors.affiliation: c Institute of Education , National Chiao Tung University.
authors.forename: Jr Huang
authors.initials: JH
authors.lastname: Lin
authors.affiliation: b Department of Educational Psychology , Texas A&M University.
authors.forename: Sandra
authors.initials: S
authors.lastname: Acosta
mesh_terms: D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D055361:Multilevel Analysis / Q000379:methods*