Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis.

By Herbert W. Marsh, Alexandre J. S. Morin, P. Parker, Gurvinder Kaur. Annual Review of Clinical Psychology, 2014

1,726 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/061623d24f1679fc65eab5c71f152044b937bd35

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In Computer Networks and Communications

In Experimental and Cognitive Psychology

In Management Science and Operations Research

Citations in the corpus

Revisiting the Empirical Distinction Between Hedonic and Eudaimonic Aspects of Well-Being Using Exploratory Structural Equation Modeling (2016, methodology): “Constraining a majority of the factor loadings to 0 may also result in the overestimation of factor correlations, when the non-target loadings are not close to 0 (Marsh et al. 2014).”
Dark Triad traits and their structure: An empirical approach (2020, methodology): “The confirmatory variant of ESEM with the target rotation allows for targeting which loadings should be as close to zero as possible and which loadings should be freely estimated (Marsh et al. 2014).”
Associations between personality, sports participation and athletic success. A comparison of Big Five in sporting and non-sporting adults (2018, methodology): “For these reasons, the ESEM approach has been proposed to be particularly suitable for testing the dimensionality and measurement invariance for Big Five measures (Marsh et al., 2014).”
On Detecting Systematic Measurement Error in Cross-Cultural Research: A Review and Critical Reflection on Equivalence and Invariance Tests (2018, methodology): “tests of a priori factor structures as well as associations with latent factors, and multigroup tests of full measurement invariance (Marsh et al., 2014).”
Using Bifactor Exploratory Structural Equation Modeling to Test for a Continuum Structure of Motivation (2018, methodology): “Recent recommendations suggest that this issue can be solved in confirmatory applications of EFA/ESEM relying on target rotation whereby the rotation is guided by a priori expectations regarding the expected factor structure (Marsh et al., 2014; Morin et al., 2016).”
A Comparison of CFA, ESEM, and BSEM in Test Structure Analysis (2019, background): “Thus, BSEMmay be better than ESEM in situations when the latter is seriously limited by complex models and insufficient sample sizes (Marsh et al., 2014; Reis, 2017).”