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Some reflections on combining meta‐analysis and structural equation modeling
Author(s) -
Cheung Mike W.L.
Publication year - 2019
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1321
Subject(s) - structural equation modeling , meta analysis , multidisciplinary approach , computer science , statistical analysis , management science , data science , sociology , social science , mathematics , statistics , engineering , medicine , machine learning
Meta‐analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well‐established research communities, terminologies, statistical models, software packages, and journals ( Research Synthesis Methods and Structural Equation Modeling: A Multidisciplinary Journal ). In this paper, I will provide some personal reflections on combining meta‐analysis and SEM in the forms of meta‐analytic SEM and SEM‐based meta‐analysis. The critical contributions of Becker (1992), Shadish (1992), and Viswesvaran and Ones (1995) in the early development of meta‐analytic SEM are highlighted. Another goal of the paper is to illustrate how meta‐analysis can be extended and integrated with other techniques to address new research questions such as the analysis of Big Data. I hope that this paper may stimulate more research development in the area of combining meta‐analysis and SEM.