Power analysis for experimental research : a practical guide for the biological, medical, and social sciences / / R. Barker Bausell, Yu-Fang Li [[electronic resource]]

• Record Nr.: UNINA9910450530803321
• Autore: Bausell R. Barker <1942->
• Pubbl/distr/stampa: Cambridge : , : Cambridge University Press, , 2002
• ISBN: 1-107-13182-0; 1-280-43379-5; 9786610433797; 0-511-33125-8; 1-139-14756-0; 0-511-17041-6; 0-511-06403-9; 0-511-05770-9; 0-511-54193-7; 0-511-07249-X
• Descrizione fisica: 1 online resource (xi, 363 pages) : digital, PDF file(s)
• Disciplina: 610/.7/2
• Soggetti: Medicine - Research - Statistical methods; Statistical power analysis
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Title from publisher's bibliographic system (viewed on 05 Oct 2015).
• Nota di bibliografia: Includes bibliographical references (p. 358-361) and index.
• Nota di contenuto: The conceptual underpinnings of statistical power -- Strategies for increasing statistical power -- General guidelines for conducting a power analysis -- The t-test for independent samples -- The paired t-test -- One-way between subjects analysis of variance -- One-way between subjects analysis of covariance -- One-way repeated measures analysis of variance -- Interaction effects for factorial analysis of variance -- Power analysis for more complex designs -- Other power analytic issues and resources for addressing them.
• Sommario/riassunto: 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.