How Many Subjects?: Statistical Power Analysis In Research

"This book fills a large gap in the applied statistics literature and, at the same time, provides empirical researchers with the means to quickly determine a valuable piece of information, namely: what sample size is needed for a particular study. "If this book only presented the reader with a straightforward set of procedures for determining N for any particular research design, it would have fulfilled its mission successfully. But the book does more. . . . How Many Subjects? has much to offer the careful and interested reader." --from the Foreword by Victor H. Denenberg "How Many Subjects? provides a 'cookbook' enabling researchers to plan an analysis that gives their alternative or research hypotheses a reasonable chance of being supported . . . useful to those with limited statistical background who simply need a guide to evaluating the power of a test contained in others' research, or to selecting the proper sample size to achieve a given level of power in their own research." --Contemporary Sociology "Until now no broad framework has existed to treat power in a unified fashion across hypothesis testing techniques. . . . An excellent contribution to the literature. . . . A valuable reference book. . . . A nice addition to the statistical literature. How Many Subjects? should be at the disposal of teachers and students of statistics." --Applied Psychological Measurement "This is a simple introduction for non-statisticians to power analysis and sample size determination. Helena Chmura Kraemer and Sue Thiemann have produced an easily readable book that clearly illustrates why sample sizes need to be sufficiently large, so that the experiment has good power properties and hence lowtype II error rates. . . . This book is an excellent introduction to the problem and whets the appetite to find out more." --The Statistician "A success. . . . For graduate students, there is no question about the book's value. I think that all graduate students should be advised to read this book before starting significant projects such as a dissertation." --Journal of Marketing Research The authors introduce a simple technique of statistical power analysis that allows researchers to compute approximate sample sizes and power for a wide variety of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons, emphasized throughout the book, demonstrate some important principles of design, measurement, and analysis that are rarely discussed in courses or textbooks. This book therefore serves not merely as a "how-to" reference for sample size calculations but also as a guide to some general principles of cost-effective research.