Effect Sizes for Research

Effect Sizes for Research
Author :
Publisher : Psychology Press
Total Pages : 253
Release :
ISBN-10 : 9780805850147
ISBN-13 : 0805850147
Rating : 4/5 (47 Downloads)

Book Synopsis Effect Sizes for Research by : Robert J. Grissom

Download or read book Effect Sizes for Research written by Robert J. Grissom and published by Psychology Press. This book was released on 2005 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Effect Sizes for Research emphasizes a practical approach through: * worked examples using real data; * formulas and rationales for a variety of variables, designs, and purposes to help readers apply the material to their own data sets; * software references for the more tedious calculations; and * informative figures and tables, questions, and over 300 references. 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.


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