In summary, provides the most comprehensive treatment of meta-analysis methods of the three texts. The real strength of text is its attention to conceptual explanations of the methods of meta-analysis. It includes chapters on methods typically used in medicine such as cumulative meta-analysis, and direct methods for combining odds ratios. , the newest of the three texts, provides a hybrid treatment of meta-analytic techniques drawing from both the social sciences and medicine. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice." The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The reader can comfortably skip the formulas and still understand their application and underlying motivation. "The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. My students raved about the clarity of the explanations and examples."ĭavid 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 book is ideal as a course textbook or for self-study. "A superb combination of lucid prose and informative graphics, the authors provide a refreshing depar- ture from cookbook approaches with their clear explanations of the what and why of meta-analysis. Blomquist Distinguished Professor Emeritus of Psychology and Neuroscience, Editor-in-chief of the American Psychologist, former editor of Psychological Bulletin As the editor-in-chief of the American Psychologist and former editor of Psychological Bulletin, I can say without hesitation that the quality of manuscript submissions reporting meta-analyses would be vastly better if researchers read this book."
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The authors address a series of common mistakes and explain how to avoid them. "This book offers the reader a unified framework for thinking about meta-analysis, and then discusses all elements of the analysis within that framework.
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Includes access to a companion website containing videos, spreadsheets, data files, free software for prediction intervals, and step-by-step instructions for performing analyses using Comprehensive Meta-Analysis (CMA).Discusses controversies in meta-analysis.Explains how to avoid common mistakes in meta-analysis.Demonstrates how to assess and interpret variation in effect size across studies.
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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. This is the same approach that we will be taking in the course. 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. Importantly, we use the formulas to inform the concepts. While the book focuses on concepts, it also includes all the relevant formulas. In fact, this has been Amazon's best-selling book on Meta-Analysis since the 1st edition was released, and to date has sold more than 12,000 copies. The book takes a conceptual approach to meta-analysis, and for this reason has been widely embraced by the research community. 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. Introduction to Meta-Analysis, 2nd Edition