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This practical guide to conducting statistical power analyses was written for students and researchers with limited quantitative backgrounds.
This practical guide to conducting statistical power analyses was written for students and researchers with limited quantitative backgrounds. The book focuses on conducting power analyzes using SPSS. The author provides detailed calculations and comments on what goes where and how it got there. Readers will appreciate the detailed coverage of topics that are not well described in competing books such as estimating effect sizes, power for complex designs, as well as common research designs such as multifactor ANOVA and multiple regression. Practical issues such as how to increase power without increasing sample size, how to report findings and run a sample analyses, how to derive effect size expectations and other statistical values, and how to support null hypotheses, are addressed throughout. Unlike competing texts, this book focuses on the statistical and methodological aspects of the analyses.
The book shows how to perform analyses using software applications rather than complex hand calculations. To facilitate application and usability, ready-to-use SPSS tools for conducting analyses are included. SPSS syntax to perform most calculations is available on the book's website. Each SPSS syntax protocol included requires only minor modification to complete the analyses. The syntax is accompanied by detailed annotations that spell out what readers need to change to conduct analyses. As such, the text reviews both power analysis techniques and tools for conducting analyzes. Numerous examples enhance accessibility by demonstrating specific issues that must be addressed at all stages of the power analysis. Chapter summaries and key statistics sections also aid in understanding the material.
The book provides three approaches to calculating power-estimation of power, hand calculations with SPSS to calculate power, and the use of SPSS syntax to calculate power. All of the SPSS 17.0 (PASW 17.0) syntax files presented in the book were tested against results produced by several other commercial and freeware programs. Chapter 1 reviews significance testing and introduces power. Chapters 2 through 9 cover power analysis strategies for a variety of common designs. Precision analysis for confidence intervals around mean difference, correlations, and effect sizes is the focus of chapter 10. The book concludes with a review of how to report power analyses, freeware and commercial software for power analyses, and how to increase power without increasing sample size. Chapters focusing on simpler analyses such as t-tests present detailed formulae and calculation examples. Chapters focusing on more complex topics present only computer-based analyses.
Intended as a supplementary text for graduate-level research methods, experimental design, quasi-experimental methods, psychometrics, statistics, advanced statistics, and/or multivariate statistics taught in the behavioral, social, biological, and medical sciences, researchers in these fields will also appreciate this book's practical emphasis. A prerequisite of introductory statistics is recommended.