A new look at the big five factor structure through exploratory structural equation modeling.

By Herbert W. Marsh, O. Lüdtke, B. Muthén, T. Asparouhov, Alexandre J. S. Morin, Ulrich Trautwein, Benjamin Nagengast. Psychological Assessment, 2010

911 citations recorded by the source corpus.

Subfields: Clinical Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/83f3589c53cf95e69aba1058e062edfe05e21ca4

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In Clinical Psychology

In Experimental and Cognitive Psychology

Citations in the corpus

Refining the theory of basic individual values. (2012, background): “The second circle from the center indicates the boundaries between the four higher order values into which values can be 8 The same problem affects various psychological constructs that seek to provide comprehensive coverage of the personality domain (e.g., Marsh et al., 2010). grouped.”
Revisiting the Empirical Distinction Between Hedonic and Eudaimonic Aspects of Well-Being Using Exploratory Structural Equation Modeling (2016, methodology): “In line with previous applications of ESEM (e.g., Marsh et al. 2010), an oblique geomin rotation was used.”
Perceived information and communication technology (ICT) demands on employee outcomes: the moderating effect of organizational ICT support. (2012, methodology): “We conducted an Exploratory Structural Equation Modeling analysis (ESEM; Asparouhov & Muthén, 2009; Marsh et al., 2010; Marsh et al., 2009), using MPlus version 5.”
Bayesian Structural Equation Modeling With Cross-Loadings and Residual Covariances (2015, background): “Recent statistical literature on measurement models including cross-loadings (Marsh et al., 2009, 2010, 2014; Morin et al., in press) show that factor correlations tend to be upwardly biased when true cross-loadings are constrained to be zero.”
Assessing Model Fit: Caveats and Recommendations for Confirmatory Factor Analysis and Exploratory Structural Equation Modeling (2015, methodology): “This was demonstrated by Marsh et al. (2010), who assessed the 60-item NEO Five-Factor Inventory using CFA and ESEM methods.”
The grounded psychometric development and initial validation of the Health Literacy Questionnaire (HLQ) (2013, background): “0 to provide inflated estimates of inter-factor correlations [44], correlations of up to 0.”
Exploratory structural equation modeling: an integration of the best features of exploratory and confirmatory factor analysis. (2014, methodology): “Although Marsh et al. (2009, 2010) used an ε value of 0.5 with complex measurement instruments so as to avoid inflated factor correlations, Asparouhov & Muthén (2009) recommend comparing solutions based on varying ε values.”
Evaluating Model Fit With Ordered Categorical Data Within a Measurement Invariance Framework: A Comparison of Estimators (2014, methodology): “Due to the poor performance of Chen’s (2007) criteria, only findings associated with Meade et al.’s (2008) cutoff criteria were reported, along with the TLI equal to zero proposed by Marsh et al. (2010).”
Using Bifactor Exploratory Structural Equation Modeling to Test for a Continuum Structure of Motivation (2018, background): “Over and above the intuitive appeal of clearly defined concepts, measured by a small number of items perfectly designed to assess a single construct, has come a recent recognition that the ideals pursued through a CFA approach are often impossible to achieve in applied research (e.g., Marsh et al., ”