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Direct linkTimothy R. Konold; Elizabeth A. Sanders – Measurement: Interdisciplinary Research and Perspectives, 2024
Compared to traditional confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM) has been shown to result in less structural parameter bias when cross-loadings (CLs) are present. However, when model fit is reasonable for CFA (over ESEM), CFA should be preferred on the basis of parsimony. Using simulations, the current…
Descriptors: Structural Equation Models, Factor Analysis, Factor Structure, Goodness of Fit
Download full textKelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
Timothy R. Konold; Elizabeth A. Sanders – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Within the frequentist structural equation modeling (SEM) framework, adjudicating model quality through measures of fit has been an active area of methodological research. Complicating this conversation is research revealing that a higher quality measurement portion of a SEM can result in poorer estimates of overall model fit than lower quality…
Descriptors: Structural Equation Models, Reliability, Bayesian Statistics, Goodness of Fit
