This authored book presents a simple and general method for conducting statistical power analysis based on the widely used F statistic. The book illustrates how these analyses work and how they can be applied to problems of studying design, to evaluate others' research, and to choose the appropriate criterion for defining "statistically significant" outcomes. Statistical Power Analysis examines the four major applications of power analysis, concentrating on how to determine: * the sample size needed to achieve desired levels of power; * the level of power that is needed in a study; * the size of effect that can be reliably detected by a study; * sensible criteria for statistical significance. Highlights of the second edition include: * a CD with an easy-to-use statistical power analysis program; * a new chapter on power analysis in multi-factor ANOVA, including repeated-measures designs; * a new One-Stop PV Table to serve as a quick reference guide. The previous edition was the first book to discuss in detail the application of power analysis to both traditional null hypothesis tests and to minimum-effect testing. This book demonstrates how the same basic model applies to both types of testing and explains how some relatively simple procedures allow researchers to ask a series of important questions about their research. Drawing from the behavioral and social sciences, the authors present the material in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtain the values needed to carry out the power analysis for a range of hypotheses. (Author/publisher)
Samenvatting