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Power analysis for experimental research : = a practical guide for the biological, medical, and social sciences /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Power analysis for experimental research :/ R. Barker Bausell, Yu-Fang Li.
Reminder of title:	a practical guide for the biological, medical, and social sciences /
Author:	Bausell, R. Barker,
other author:	Li, Yu-Fang,
Description:	1 online resource (xi, 363 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:	Medicine - Research -
Online resource:	https://doi.org/10.1017/CBO9780511541933
ISBN:	9780511541933 (ebook)

Power analysis for experimental research : = a practical guide for the biological, medical, and social sciences /
Bausell, R. Barker,1942-

Power analysis for experimental research :a practical guide for the biological, medical, and social sciences /R. Barker Bausell, Yu-Fang Li. - 1 online resource (xi, 363 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

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.

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.

ISBN: 9780511541933 (ebook)Subjects--Topical Terms:

672001
Medicine
--Research

LC Class. No.: R853.S7 / B375 2002

Dewey Class. No.: 610/.7/2

Power analysis for experimental research : = a practical guide for the biological, medical, and social sciences /
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505 0 $a 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.
520 $a 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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