Effect Sizes for Research
Univariate and Multivariate Applications
Published April 4th 2005 by Routledge – 272 pages
The goal of this book is to inform a broad readership about a variety of measures and estimators of effect sizes for research, their proper applications and interpretations, and their limitations. Its focus is on analyzing post-research results. The book provides an evenhanded account of controversial issues in the field, such as the role of significance testing. Consistent with the trend toward greater use of robust statistical methods, the book pays much attention to the statistical assumptions of the methods and to robust measures of effect size.
Effect Sizes for Research discusses different effect sizes for a variety of kinds of variables, designs, circumstances, and purposes. It covers standardized differences between means, correlational measures, strength of association, and confidence intervals. The book clearly demonstrates how the choice of an appropriate measure might depend on such factors as whether variables are categorical, ordinal, or continuous; satisfying assumptions; the sampling method; and the source of variability in the population.
It emphasizes a practical approach through:
Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is an excellent supplement for advanced courses in statistics in disciplines such as psychology, education, the social sciences, business, management, and medicine. A prerequisite of introductory statistics through factorial analysis of variance and chi-square is recommended.
"…the book is a study in absolute clarity. Overall, Grissom and Kim have presented a tour de force treatment of effect sizes that is accurately described in their subtitle as being both broad and practical." - Applied Psychological Measurement
"No other current book provides the broad overview of effect size measures contained in this book….I am especially impressed by the authors knowledge of the latest developments in the literature….The level is appropriate for a broad range of readers….I would use it regularly to advise colleagues and students how to calculate and interpret various effect size measures. The publication of this book might stimulate us to offer a separate course on effect size measures." - Scott E. Maxwell, Ph.D., University of Notre Dame
"I strongly recommend this book for anyone who wishes to conduct research based on reason and not luck….The quality of the scholarship is excellent….The level is appropriate for an upper class undergraduate through doctoral reading audience….it would be valuable throughout the social and behavioral sciences, medicine, nursing, etc….I would use this [book] as supplemental reading for all six stat courses I teach." - Shlomo S. Sawilowsky, Ph.D., Wayne State University
"The coverage and depth of this book is exceptional. I learned several new things just by reviewing a handful of chapters….The examples are…excellent in terms of their context and applicability….I can easily see this book used as a supplement in…[a variety of] courses…a valuable reference for researchers, practitioners, and graduate students." - Allen Huffcutt, Ph.D., Bradley University
Preface. Introduction. Confidence Intervals for Comparing the Averages of Two Groups. The Standardized Difference Between Means. Correlational Effect Sizes for Comparing Two Groups. Effect Size Measures That Go Beyond Comparing Two Centers. Effect Sizes for One-Way ANOVA Designs. Effect Sizes for Factorial Designs. Effect Sizes for Categorical Variables.Effect Sizes for Ordinal Categorical Variables.
Robert J. Grissom is a Professor Emeritus and Adjunct Professor of Psychology at San Francisco State University and a Consultant in Statistics. He received his Ph.D. in Psychology from Princeton University. Co-founder of the Graduate Program in Psychological Research at San Francisco State, Dr. Grissom has written numerous chapters and articles on effect size methodology.
John J. Kim is a Professor of Psychology at San Francisco State University. He received his Ph.D. from the Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology in 1993. The current Associate Vice President for Academic Resources at San Francisco State, Dr. Kim has written numerous chapters and articles on effect size methodology.