The Growth of Structural Equation Modeling: 1994-2001

By Scott L. Hershberger. 2003

193 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/2924cd7992e0dcc61332d1972263576f05015d4e

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In Experimental and Cognitive Psychology

In Management Science and Operations Research

Citations in the corpus

Structural equation modeling: strengths, limitations, and misconceptions. (2005, methodology): “…number of published articles that have used SEM appearing in psychological journals (including common publication outlets for clinical scientists) (Hershberger 2003); (b) evidence that SEM has become the multivariate technique most commonly used by psychologists (Hershberger 2003); (c) evidence…”
Structural equation modeling in medical research: a primer (2010, background): “Indeed, it has become “the preeminent multivariate technique” [4] and is now accessible on-line at no cost (e.”
Testing for Measurement and Structural Equivalence in Large-Scale Cross-Cultural Studies: Addressing the Issue of Nonequivalence (2010, methodology): “From reviews of the SEM literature (see Austin & Calderón, 1996; Hershberger, 2003; Tremblay & Gardner, 1996), it is evident that the past two decades have witnessed rapidly increasing use of SEM procedures in general and as they apply to tests for multigroup equivalence in particular (see…”
A critical review of structural equation modeling applications in construction research (2015, background): “In comparison, SEM applications in marketing and psychology grew linearly over time without acceleration [6,29], while applications in operations management did not grow linearly but accelerated over time.”
Use of structural equation modeling in operations management research: Looking back and forward ☆ (2006, background): “In contrast, the use of SEM in marketing and psychology grew steadily over time and there is no indication of its accelerated use in more recent years (Baumgartner and Homburg, 1996; Hershberger, 2003).”
BEST PRACTICES IN STRUCTURAL EQUATION MODELING (2007, methodology): “Indeed, with the continued development of SEM software packages such as AMOS (Arbuckle, 2007), EQS (Bentler, 2006), LISREL (Joreskog & Sorbom, 2006), and Mplus (Muthen & Muthen, 2006), SEM “has become the preeminent multivariate method of data analysis” ( Hershberger, 2003, pp. 43 –44).”
A Two-Stage Approach to Synthesizing Covariance Matrices in Meta-Analytic Structural Equation Modeling (2009, methodology): “Structural equation modeling (SEM) is widely used as a statistical framework to test models involving observed and latent variables in behavioral and social sciences (eg, Hershberger, 2003 ; Tremblay & Gardner, 1996 ).”
A Note on Sample Size and Solution Propriety for Confirmatory Factor Analytic Models (2013, background): “The question of minimum required sample size for use in latent variable modeling is an important issue, particularly when considering the popularity of structural equation modeling (SEM) techniques (Breckler, 1990; Hershberger, 2003; Martens, 2005; Tremblay & Gardner, 1996).”
EIGHT MYTHS ABOUT CAUSALITY AND STRUCTURAL EQUATION MODELS (2013, background): “Thus, interest in SEMs is high and continues to grow (e.g., Hershberger 2003; Schnoll et al. 2004; Shah and Goldstein 2006).”
Reporting practices in confirmatory factor analysis: an overview and some recommendations. (2009, background): “Hershberger (2003) noted the number of substantive and technical SEM articles referenced in the PsychINFO database increased by a factor of approximately 2.5 from 1994 to 2001.”