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Meta-Analysis: A Structural Equation Modeling Approach by Mike W.-L. Cheung

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Chapter 1Introduction

This chapter gives an overview of this book. It first briefly reviews the history and applications of meta-analysis and structural equation modeling (SEM). The importance of using meta-analysis and SEM to advancing scientific research is discussed. This chapter then addresses the needs and advantages of integrating meta-analysis and SEM. It further outlines the remaining chapters and the data sets used in the book. We close this chapter by addressing topics that will not be further discussed in this book.

1.1 What is meta-analysis?

Pearson (1904) was often credited as one of the earliest researchers applying ideas of meta-analysis (e.g., Chalmers et al., 2002; Cooper and Hedges, 2009; National Research Council, 1992; O'Rourke, 2007). He tried to determine the relationship between mortality and inoculation with a vaccine for enteric fever by averaging correlation coefficients across 11 small-sample studies. The idea of combining and pooling studies has been widely used in the physical and social sciences. There are many successful stories as documented in, for example, National Research Council (1992) and Hunt (1997). The term meta-analysis was coined by Gene Glass in educational psychology to represent “the statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings” (Glass 1976, p.3).

Validity generalization, another technique with similar objectives, was independently developed by ...

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