Book contents
- Frontmatter
- Contents
- Introduction
- 1 The conceptual underpinnings of statistical power
- 2 Strategies for increasing statistical power
- 3 General guidelines for conducting a power analysis
- 4 The t-test for independent samples
- 5 The paired t-test
- 6 One-way between subjects analysis of variance
- 7 One-way between subjects analysis of covariance
- 8 One-way repeated measures analysis of variance
- 9 Interaction effects for factorial analysis of variance
- 10 Power analysis for more complex designs
- 11 Other power analytic issues and resources for addressing them
- Technical appendix
- Bibliography
- Index
Introduction
Published online by Cambridge University Press: 28 August 2009
- Frontmatter
- Contents
- Introduction
- 1 The conceptual underpinnings of statistical power
- 2 Strategies for increasing statistical power
- 3 General guidelines for conducting a power analysis
- 4 The t-test for independent samples
- 5 The paired t-test
- 6 One-way between subjects analysis of variance
- 7 One-way between subjects analysis of covariance
- 8 One-way repeated measures analysis of variance
- 9 Interaction effects for factorial analysis of variance
- 10 Power analysis for more complex designs
- 11 Other power analytic issues and resources for addressing them
- Technical appendix
- Bibliography
- Index
Summary
The primary purpose of this book is to provide an easy-to-use, unified approach to statistical power analysis in order to enable investigators to avail themselves of the advantages of this powerful tool in the design of their experiments. It is our firm conviction that no other process possesses more potential for increasing the scientific and societal yields accruing from our experiments. It is also our firm belief that the a priori consideration of power is so integral to the entire design process that its consideration should not be delegated to individuals not integrally involved in the conduct of an investigation, hence the present volume has been written to be completely accessible to practicing researchers. For this reason we have studiously avoided the use of technical terms and formulas until the appendix to make it as accessible (and hopefully interesting) to individuals without advanced statistical training as possible.
This is not to say that statistical collaboration in the conduct of most experiments is not desirable. It is, in fact, often absolutely essential and we have written this work to make it as helpful as possible to statisticians charged with the task of performing a power or sample size analysis. It has been our experience, however, that while principal investigators are well versed in formulating research hypotheses, they often conceptualize the determination of power (or the sample size necessary to achieve a desired value thereof) as a technical exercise better delegated to someone with the appropriate expertise.
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- Chapter
- Information
- Power Analysis for Experimental ResearchA Practical Guide for the Biological, Medical and Social Sciences, pp. ix - xiiPublisher: Cambridge University PressPrint publication year: 2002
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