Power Analysis for Experimental Research: A Practical Guide for the Biological, Medical and Social Sciences

R. Barker Bausell; Yu-Fang Li

doi:10.1017/CBO9780511541933

Power analysis is an essential tool for determining whether a statistically significant result can be expected in a scientific experiment prior to the experiment being performed. Many funding agencies and institutional review boards now require power analyses to be carried out before they will approve experiments, particularly where they involve the use of human subjects. This comprehensive, yet accessible, book provides practising researchers with step-by-step instructions for conducting power/sample size analyses, assuming only basic prior knowledge of summary statistics and the normal distribution. It contains a unified approach to statistical power analysis, with numerous easy-to-use tables to guide the reader without the need for further calculations or statistical expertise. This will be an indispensable text for researchers and graduates in the medical and biological sciences needing to apply power analysis in the design of their experiments.

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Contents

Frontmatter
pp i-vi
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Contents
pp vii-viii
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Introduction
pp ix-xii
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1 - The conceptual underpinnings of statistical power
pp 1-15
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2 - Strategies for increasing statistical power
pp 16-35
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3 - General guidelines for conducting a power analysis
pp 36-49
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4 - The t-test for independent samples
pp 50-56
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5 - The paired t-test
pp 57-70
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6 - One-way between subjects analysis of variance
pp 71-110
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7 - One-way between subjects analysis of covariance
pp 111-178
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8 - One-way repeated measures analysis of variance
pp 179-238
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9 - Interaction effects for factorial analysis of variance
pp 239-301
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10 - Power analysis for more complex designs
pp 302-328
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11 - Other power analytic issues and resources for addressing them
pp 329-340
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Technical appendix
pp 341-357
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Bibliography
pp 358-361
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Index
pp 362-363
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Power Analysis for Experimental Research

A Practical Guide for the Biological, Medical and Social Sciences

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Contents

Frontmatter
pp i-vi

Contents
pp vii-viii

Introduction
pp ix-xii

1 - The conceptual underpinnings of statistical power
pp 1-15

2 - Strategies for increasing statistical power
pp 16-35

3 - General guidelines for conducting a power analysis
pp 36-49

4 - The t-test for independent samples
pp 50-56

5 - The paired t-test
pp 57-70

6 - One-way between subjects analysis of variance
pp 71-110

7 - One-way between subjects analysis of covariance
pp 111-178

8 - One-way repeated measures analysis of variance
pp 179-238

9 - Interaction effects for factorial analysis of variance
pp 239-301

10 - Power analysis for more complex designs
pp 302-328

11 - Other power analytic issues and resources for addressing them
pp 329-340

Technical appendix
pp 341-357

Bibliography
pp 358-361

Index
pp 362-363

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Power Analysis for Experimental Research

A Practical Guide for the Biological, Medical and Social Sciences

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