The Essential Guide to Effect Sizes

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.

Paul D. Ellis is a professor in the Department of Management and Marketing at Hong Kong Polytechnic University, where he has taught research methods for fifteen years. His research interests includes 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.

List of figures	p. ix
List of Tables	p. x
List of boxes	p. xi
Introduction	p. xiii
Effect sizes and the interpretation of results	p. 1
Introduction to effect sizes	p. 3
The dreaded question	p. 3
Two families of effects	p. 6
Reporting effect size indexes - three lessons	p. 16
Summary	p. 24
Interpreting effects	p. 31
A age-old debate - rugby versus soccer	p. 31
The problem of interpretation	p. 32
The importance of context	p. 35
The contribution to knowledge	p. 38
Cohen's controversial criteria	p. 40
Summary	p. 42
The analysis of statistical power	p. 45
Power analysis and the detection of effects	p. 47
The foolish astronomer	p. 47
The analysis of statistical power	p. 56
Using power analysis to select sample size	p. 61
Summary	p. 66
The painful lessons of power research	p. 73
The low power of published research	p. 73
How to boost statistical power	p. 81
Summary	p. 82
Meta-analysis	p. 87
Drawing conclusions using meta-analysis	p. 89
The problem of discordant results	p. 89
Reviewing past research - two approaches	p. 90
Meta-analysis in six (relative) easy steps	p. 97
Meta-analysis as a guide for further research	p. 109
Summary	p. 112
Minimizing bias in meta-analysis	p. 116
Four ways to ruin perfectly good meta-analysis	p. 116
Exclude relevant research	p. 117
Include bad results	p. 122
Use inappropriate statistical models	p. 127
Run analyses with insufficient statistical power	p. 130
Summary	p. 131
Last word: thirty recommendations for researchers	p. 134
Appendices
Minimum sample size	p. 138
Alternative methods for meta-analysis	p. 141
Bibliography	p. 153
Index	p. 170
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The Essential Guide to Effect Sizes

Summary

Author Biography

Table of Contents

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