How many subjects?: statistical power analysis in research

By:

Kraemer, Helena Chmura

Contributor(s):

Thiemann, Sue

Publication details: Newbury Park SAGE Publications 1987Description: 120; ill.,bibl.; BookFindISBN:

0803929498

Subject(s):

STATISTICS, methods

Contents:

CHAPTER 1 Introduction CHAPTER 2 General Concepts CHAPTER 3 The Pivotal Case Intraclass Correlation CHAPTER 4 Equality of News Z- and T- tests, Balanced ANOVA CHAPTER 5 Correlation Coefficients CHAPTER 6 Linear Regression CHAPTER 7 Homogeneity of Variance Tests CHAPTER 8 Binomial Tests CHAPTER 9 Contingency Table Analysis CHAPTER 10 Conclusions.

Summary: HardbackSummary: How Many Subjects? is a practical guide to sample size calculations and general principles of cost-effective research. It introduces a simple technique of statistical power analysis which allows researchers to compute approximate sample sizes and power for a wide variety of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons, emphasized throughout the book, demonstrate important principles of design, measurement and analysis that are rarely discussed in courses or textbooks.

Holdings
Item type	Home library	Class number	Status	Date due	Barcode
Book	Newcomb Library at Homerton Healthcare Shelves	WA 950 KRA (Browse shelf(Opens below))	Available		HOM0928

Hardback

How Many Subjects? is a practical guide to sample size calculations and general principles of cost-effective research. It introduces a simple technique of statistical power analysis which allows researchers to compute approximate sample sizes and power for a wide variety of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons, emphasized throughout the book, demonstrate important principles of design, measurement and analysis that are rarely discussed in courses or textbooks.

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