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How many subjects? : statistical power analysis in research /

By: Kraemer, Helena Chmura
Title By: Blasey, Christine
Material type: BookPublisher: Los Angeles : Sage Publicastions, Inc., c2016.Edition: 2nd ed.Description: xiii, 140 p. : ill. ; 23 cm.ISBN: 9781483319544Subject(s): Research -- Statistical methods | Statistical power analysisDDC classification: 001.4/22
Summary:
With increased emphasis on helping readers understand the context in which power calculations are done, this Second Edition of How Many Subjects? by Helena Chmura Kraemer and Christine Blasey introduces a simple technique of statistical power analysis that allows researchers to compute approximate sample sizes and power for a wide range of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can then easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons demonstrate important principles of design, measurement, and analysis that are rarely discussed in courses or textbooks, making this book a valuable instructional resource as well as a must-have guide for frequent reference.
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Item type Home library Call number Status Date due Barcode Item holds
REGULAR University of Wollongong in Dubai
PHD Shelf
001.422 KR HO (Browse shelf) Available T0051728
Total holds: 0

Includes bibliographical references (p. 129-131) and index.

The rules of the game -- General concepts -- The pivotal case : interclass correlation -- Equality of means : Z- and T-test, balanced anova -- Correlation coefficients -- Linear regression analysis -- Homogeneity of variance tests -- Binomial tests -- Contingency table analysis -- Wrap-up.

With increased emphasis on helping readers understand the context in which power calculations are done, this Second Edition of How Many Subjects? by Helena Chmura Kraemer and Christine Blasey introduces a simple technique of statistical power analysis that allows researchers to compute approximate sample sizes and power for a wide range of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can then easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons demonstrate important principles of design, measurement, and analysis that are rarely discussed in courses or textbooks, making this book a valuable instructional resource as well as a must-have guide for frequent reference.

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