%0 Journal Article %A Marsh, Herbert W. %A Guo, Jiesi %A Dicke, Theresa %A Parker, Philip D. %A Craven, Rhonda G. %D 2020 %T Confirmatory Factor Analysis (CFA), Exploratory Structural Equation Modeling (ESEM), and Set-ESEM: Optimal Balance Between Goodness of Fit and Parsimony %U https://tandf.figshare.com/articles/journal_contribution/Confirmatory_Factor_Analysis_CFA_Exploratory_Structural_Equation_Modeling_ESEM_and_Set-ESEM_Optimal_Balance_Between_Goodness_of_Fit_and_Parsimony/8283392 %R 10.6084/m9.figshare.8283392.v2 %2 https://tandf.figshare.com/ndownloader/files/15508385 %K Confirmatory factor analysis %K exploratory structural equation modeling %K multigroup factorial invariance %K longitudinal factorial invariance %K multitrait-multimethod analysis %X

CFAs of multidimensional constructs often fail to meet standards of good measurement (e.g., goodness-of-fit, measurement invariance, and well-differentiated factors). Exploratory structural equation modeling (ESEM) represents a compromise between exploratory factor analysis’ (EFA) flexibility, and CFA/SEM’s rigor and parsimony, but lacks parsimony (particularly in large models) and might confound constructs that need to be kept separate. In Set-ESEM, two or more a priori sets of constructs are modeled within a single model such that cross-loadings are permissible within the same set of factors (as in Full-ESEM) but are constrained to be zero for factors in different sets (as in CFA). The different sets can reflect the same set of constructs on multiple occasions, and/or different constructs measured within the same wave. Hence, Set-ESEM that represents a middle-ground between the flexibility of traditional-ESEM (hereafter referred to as Full-ESEM) and the rigor and parsimony of CFA/SEM. Thus, the purposes of this article are to provide an overview tutorial on Set-ESEM, juxtapose it with Full-ESEM, and to illustrate its application with simulated data and diverse “real” data applications with accessible, heuristic explanations of best practice.

%I Taylor & Francis