 | Summaries and Customer Reviews are supplied by Amazon.com | 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 |
Average Customer Rating:  Very readable explanations on meta-analysis Introduction to Meta-Analysis (Statistics in Practice)
The book Introduction to Meta-Analysis by Dr. Borenstein, is great book. This may be surprising for a statistic book, but the authors make the process of conducting a meta-analysis very understandable. They have all the formulas, will indexed, in a logical order and explain where the formulas came from. They then work simple examples that are easy to follow. The book gets into more meat in the meta regression area and further clarifies how to leverage the meta-analysis to understand subgroups. I also bought the software Comprehensive Meta-analysis that goes with the book. I plan to buy Dr. Borenstein's next book, which I assume is more advanced. just the right time for this book Meta-analysis is becoming more and more important in medical research. In my current job I am working on two projects where I am constructing meta-analyses. The pioneering book on this topic was the book by Hedges and Olkin which was the first to put statistical rigor to research synthesis which had previously been done using very ad hoc methods. I have in the past had experience with using published p-values for combination in meta-analysis. It has been more than twenty years since that book came out. You can look a my listmania on meta-analysis to see the various books thyat are currently on the market. Many are theoretical but do not give a good feel for applications. Various approaches have been proposed. There are texts on Bayesian meta-analyse and meta-analyses based on the profile likelihood approach. Some cover p-value combination tests. Some cover special topics such as effect size estimation, mixed modeling approaches.
This book is introductory and is written so clearly that it is useful to research statisticians and novices. Anyone interested in learning about meta-analysis can go to this book and learn a lot from it. Its outstanding features include its organization which divides the text into 10 topicla areas. Each area contains several chapters. Each chapter begins with an introduction and ends with a review of keypoints in bullet form. Key equations are laid out in boxes. The writing is clear and concise. Important concepts are covered first. While the coverage emphasizes methods that combine effect sizes from multiple studies the coverage is very comprehensive and all approaches and issues are touched on or discussed in detail. The authors provide many well-illustrated worked-out examples to illustrate the techniques and reinforce the material that is learned. Many useful and important applications are given. It includes a very good bibliography and sections with recommended reading lists. Biostats, Inc. the corporation that author Berensteinis the president of, has produced software that ios available to help guide users of meta-analysis and is availble for a trial period to anyone who buys the text.
This is the right book at the right time. Anyone starting to learn about meta-analysis from scratch should consult this book first. I will treasure it as a reference source and look forward to testing out the software |  |
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