PDF] Fit indices in covariance structure modeling : Sensitivity to underparameterized model misspecification

This study evaluated the sensitivity of maximum likelihood (ML)-, generalized least squares (GLS)-, and asymptotic distribution-free (ADF)-based fit indices to model misspecification, under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustness theory also was examined. Standardized root-mean-square residual (SRMR) was the most sensitive index to models with misspecified factor covariance(s), and Tucker-Lewis Index (1973; TLI), Bollen's fit index (1989; BL89), relative noncentrality index (RNI), comparative fit index (CFI), and the MLand GLS-based gamma hat, McDonald's centrality index (1989; Me), and root-mean-square error of approximation (RMSEA) were the most sensitive indices to models with misspecified factor loadings. With ML and GLS methods, we recommend the use of SRMR, supplemented by TLI, BL89, RNI, CFI, gamma hat, Me, or RMSEA (TLI, Me, and RMSEA are less preferable at small sample sizes). With the ADF method, we recommend the use of SRMR, supplemented by TLI, BL89, RNI, or CFI. Finally, most of the ML-based fit indices outperformed those obtained from GLS and ADF and are preferable for evaluating model fit.

Structural Equation Modeling

Assessing the overall fit of composite models estimated by partial least squares path modeling

The factor structure of attention-deficit/hyperactivity disorder in schoolchildren

Exploratory Structural Equation Modeling of Personality Data - Tom Booth, David J. Hughes, 2014

PDF] The effect of model misspecification on overall goodness-of-fit indices for structural equation modeling

Structural equation modeling in medical research: a primer – topic of research paper in Psychology. Download scholarly article PDF and read for free on CyberLeninka open science hub.

PDF) The Relationship Between the Standardized Root Mean Square Residual and Model Misspecification in Factor Analysis Models

The Poor Fit of Model Fit for Selecting Number of Factors in Exploratory Factor Analysis for Scale Evaluation - Amanda K. Montoya, Michael C. Edwards, 2021

Exploratory structural equation modeling: a streamlined step by step approach using the R Project software, BMC Psychiatry