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The Essential Guide to Effect Sizes: Statistical Power, Meta-Analysis, and the Interpretation of Research Results, by Paul D. Ellis
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This succinct and jargon-free introduction to effect sizes gives students and researchers the tools they need to interpret the practical significance of their results. Using a class-tested approach that includes numerous examples and step-by-step exercises, it introduces and explains three of the most important issues relating to the practical significance of research results: the reporting and interpretation of effect sizes (Part I), the analysis of statistical power (Part II), and the meta-analytic pooling of effect size estimates drawn from different studies (Part III). The book concludes with a handy list of recommendations for those actively engaged in or currently preparing research projects.
- Sales Rank: #483199 in Books
- Published on: 2010-08-16
- Original language: English
- Number of items: 1
- Dimensions: 9.72" h x .39" w x 6.85" l, .85 pounds
- Binding: Paperback
- 187 pages
Review
"Assessing the substantive significance of research is essential for both scientific progress and practical implications. This authoritative and well-written book gives relevant examples of key issues and offers practical guidelines for assessing the importance of research findings. The book concludes with clear recommendations for designing and carrying out good research and for assessing and reporting research findings."
William H. Starbuck, Professor-in-Residence, University of Oregon, and Professor Emeritus, New York University
"Paul Ellis writes with a light touch, explains well, and uses numerous practical examples. He focuses on four of the issues that are central to the statistical changes now sweeping many disciplines - effect sizes, confidence intervals, power, and meta-analysis. This is a highly readable, highly practical book. It will be invaluable to anyone who wishes to contribute to - or even just understand - the research of the future."
Geoff Cumming, Emeritus Professor, School of Psychological Science, La Trobe University, Australia
About the Author
Paul D. Ellis is Professor in the Department of Management and Marketing at Hong Kong Polytechnic University, where he has taught research methods for nearly fifteen years. His research interests include trade and investment issues, marketing and economic development, international entrepreneurship, and economic geography. Professor Ellis has been ranked as one of the world's most prolific scholars in the field of international business.
Most helpful customer reviews
15 of 16 people found the following review helpful.
Excellent book!
By Andreas Schwab, Assistant Professor, Iowa State University
This practical and very accessible book addresses three key issues for the interpretation of quantitative empirical research in the social sciences:
1. How to determine if the effects observed are of substantive significance?
2. How to use power evaluations for research design and the interpretation of observed effects?
3. How to use meta analyses to draw conclusions from multiple past studies that have reported disparate effects?
In my opinion, the main advantage of this book is that it outlines answers to these questions without relying primarily on mathematical equations. Instead, the fundamental logic of the introduced logics is explained in the text and using simple examples. The focus is on introducing methodologies that have been well-established in the research methods literature to a boarder audience of social science researchers. Given the increasing recognition of the severe limitations of standard null-hypothesis significance tests, I find all three topics covered in the book important as they indicate ways how we can substantially improve the interpretation of our empirical research results. I would recommend this book to scholars, doctoral students, and practitioners interested in the advanced interpretation of empirical research findings.
10 of 11 people found the following review helpful.
Practical significance to accompany statistical significance
By Coda
This book is a very good review of including and measuring practical significance in a research effort. Before reading the book I thought it might run the risk of preaching practical significance as a way of replacing statistical significance. Dr. Ellis does not go down that path at all, in fact quite the opposite. It is a very well explained approach to the importance of paying attention to both practical and statistical significance in the same research effort.
Best of all is the chapter on Power Analysis. It is a very thorough, well explained guide to assuring proper power during the design stage of a research effort. The importance of such an analysis seems to be missing in most graduate level statistics courses, but it can serve a researcher very well.
5 of 5 people found the following review helpful.
the book also provides a good overview of the null hypothesis significance testing controversy
By Stijn Debrouwere
Exceptionally lucid overview of power analysis, effect sizes, sample size calculations and related topics. Along the way, the book also provides a good overview of the null hypothesis significance testing controversy, the problems with familywise alpha corrections like Bonferroni, publication bias, the almost-universal misinterpretation of p-values and other methodological issues. Heartily recommended as a practical guide for researchers and statisticians, but also for readers with an interest in the foundations of statistics or the sociology of science.
Most statistics courses gloss over power analysis, and after all, there's only five or six equations (or one piece of software) that you need to learn how to use, but it absolutely pays to have a methodological grasp of what it is you're doing when calculating a sample size or estimating power. Again, wonderful book.
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