About the Book
Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. Many measures and estimators are reviewed along with their application, interpretation, and limitations. Noted for its practical approach, the book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of SPSS, SAS, R, and S-Plus are provided. The book's broad disciplinary appeal results from its inclusion of a variety of examples from psychology, medicine, education, and other social sciences. Special attention is paid to confidence intervals, the statistical assumptions of the methods, and robust estimators of effect sizes. The extensive reference section is appreciated by all.
With more than 40% new material, highlights of the new editon include:
three new multivariate chapters covering effect sizes for analysis of covariance, multiple regression/correlation, and multivariate analysis of variance
more learning tools in each chapter including introductions, summaries, "Tips and Pitfalls" and more conceptual and computational questions
more coverage of univariate effect sizes, confidence intervals, and effect sizes for repeated measures to reflect their increased use in research
more software references for calculating effect sizes and their confidence intervals including SPSS, SAS, R, and S-Plus
the data used in the book are now provided on the web along with new data and suggested calculations with IBM SPSS syntax for computational practice.
Effect Sizes for Research covers standardized and unstandardized differences between means, correlational measures, strength of association, and parametric and nonparametric measures for between- and within-groups data.
Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is also an excellent supplement for advanced statistics courses in psychology, education, the social sciences, business, and medicine. A prerequisite of introductory statistics through factorial analysis of variance and chi-square is recommended.
Table of Contents:
1. Introduction 2. Confidence Intervals for Comparing the Averages of Two Groups 3. The Standardized Difference Between Means 4. Correlational Effect Sizes and Related Topics 5. Parametric and Nonparametric Effect Size Measures that Go Beyond Comparing Two Averages 6. Effect Sizes for One-Way ANOVA and Nonparametric Approaches 7. Effect Sizes for Factorial Designs 8. Effect Sizes for Categorical Variables 9. Effect Sizes for Ordinal Categorical Dependent Variables (Rating Scales) 10. Effect Sizes for Multiple Regression/Correlation 11. Effect Sizes for Analysis of Covariance 12. Effect Sizes for Multivariate Analysis of Variance
About the Author :
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.
Review :
"This book presents an excellent summary of the debate around the use of null hypothesis significance testing and includes a lot of examples and practical advice to researchers about the software and methods needed to report effect size. Coverage of different models is wide and much of the material will be highly relevant to psychologists working in many fields." - Chris Beeley, Senior Evaluation Manager, Institute of Mental Health, Nottingham, UK, in The Psychologist "This book is the single-best, definitive treatment of effect sizes, and is best characterized by the following adjectives: comprehensive, contemporary, clear, concrete, accessible, practical, and well-organized." - Bruce Thompson, Texas A&M University and Baylor College of Medicine, USA "This is THE essential guide to effect sizes and confidence intervals: authoritative yet accessible, detailed yet entirely practical. It needs to be close to the elbow of every serious researcher and graduate student." - Geoff Cumming, La Trobe University, Melbourne, Australia "Effect sizes and associated confidence intervals are increasingly recognized as a more informative basis for inferences than p-values. This helpful book introduces a wide array of tools to enable researchers to fulfill this agenda." - Robert G. Newcombe, Cardiff University, UK "This book provides accessible, comprehensive coverage of effect sizes and their interpretation. I have used the first edition as a required text for a course on interpretation of data and plan to continue to use it. Researchers, both novice and experienced, will also find the book to be a valuable reference." - Patricia A. Shewokis, Drexel University, USA "A thousand copies of this book should be dropped from a low flying airplane over ... the 4,200 college and univeristy campuses in America. ... No ... quantitative professor, researcher, or student should be without this text. ... The writing style is clear ... and a pleasure to read. This book should be required reading for all graduate faculty, students, and workers in the field." - Shlomo Sawilowsky, Wayne State University, USA "It is important for graduate students to understand effect size in multivariate statistics. ... The book presents a good theoretical background on the effect sizes for various statistical procedures and it is ... way ahead of other books. ... The authors write well... It [is] an excellent text on effect sizes. ... I would ... use the book in my course." - Aman Yadav, Purdue University, USA
