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This workshop is based on the book Introduction to Meta-Analysis (Michael Borenstein, Larry V Hedges, Julian PT Higgins, Hannah Rothstein), which was written with funding from NIH and published by Wiley in 2009.

The book takes a conceptual approach to meta-analysis, and for this reason has been widely embraced by the research community. In fact, this has been Amazon's best-selling book on Meta-Analysis since it was released, and to date has sold more than 12,000 copies.

While the book focuses on concepts, it also includes all the relevant formulas. Importantly, we use the formulas to inform the concepts. That is, we make an intuitive argument that the meta-analysis should work in a particular way, and then show how the formula matches this goal. This is the same approach that we will be taking in the course. In the course we build on this approach, using Excel, CMA, and interactive graphs to show how changes in the studies impact the study weights, the summary effect, and other statistics.

From the Back Cover

This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology.

Introduction to Meta-Analysis:

• Outlines the role of meta-analysis in the research process
  
• Shows how to compute effects sizes and treatment effects
  
• Explains the fixed-effect and random-effects models for synthesizing data
  
• Demonstrates how to assess and interpret variation in effect size across studies
• Clarifies concepts using text and figures, followed by formulas and examples
  
• Explains how to avoid common mistakes in meta-analysis
  
• Discusses controversies in meta-analysis
  
• Features a web site with additional material and exercises

"A superb combination of lucid prose and informative graphics, written by four of the world’s leading experts on all aspects of meta-analysis. Borenstein, Hedges, Higgins, and Rothstein provide a refreshing departure from cookbook approaches with their clear explanations of the ‘what and why’ of meta-analysis. The book is ideal as a course textbook or for self-study. My students, who used pre-publication versions of some of the chapters, raved about the clarity of the explanations and examples."
David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics.

"The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice."
Jesse A. Berlin, ScD

"Introduction to Meta-Analysis is an excellent resource for novices and experts alike. The book provides a clear and comprehensive presentation of all basic and most advanced approaches to meta-analysis. This book will be referenced for decades."
Michael A. McDaniel, Professor of Human Resources and Organizational Behavior, Virginia Commonwealth University

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