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

Handbook / Manual
Addresses power analysis, a poorly understood process that nevertheless must be performed prior to almost all scientific experiments
It explains a statistical process in a way that is very accessible to non-statisticians
The only text on power analysis to be aimed at the medical and biological sciences

By: R Barker Bausell (Author), Yu-Fang Li (Author)

363 pages, 6 b/w illustrations, 189 tables

Cambridge University Press

Hardback | Sep 2002 | #128059 | ISBN: 0521809169
Availability: Usually dispatched within 6 days Details
NHBS Price: £103.00 $131/€121 approx

About this book

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.<br><br>


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


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Biography

R. Barker Bausell is Professor at the University of Maryland School of Medicine and Director of Research of the Complementary Medicine Program. Yu-Fang Li is a Data Analyst at the Department of Veteran's Affairs, Puget Sound Health Care System in Seattle, Washington.

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