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The book provides a clear and comprehensive presentation of all basic and most advanced approaches to meta-analysis. See Section 11 of the Meta-analysis report for full details of these findings. Introduction to Meta-Analysis is an excellent resource for novices and experts alike. 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. 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. My students, who used pre-publication versions of some of the chapters, raved about the clarity of the explanations and examples. The book is ideal as a course textbook or for self-study. Borenstein, Hedges, Higgins, and Rothstein provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. Essential steps for meta-analysis are covered, including pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta. This book serves as an accessible introduction into how meta-analyses can be conducted in R. Features a web site with additional material and exercisesĪ superb combination of lucid prose and informative graphics, written by four of the world’s leading experts on all aspects of meta-analysis. Welcome Welcome to the online version of Doing Meta-Analysis with R: A Hands-On Guide.Discusses controversies in meta-analysis.
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Explains how to avoid common mistakes in meta-analysis.Clarifies concepts using text and figures, followed by formulas and examples.Demonstrates how to assess and interpret variation in effect size across studies.Explains the fixed-effect and random-effects models for synthesizing data.Shows how to compute effects sizes and treatment effects.Outlines the role of meta-analysis in the research process.Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology.
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This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies.