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How Many Subjects?

How Many Subjects?
Statistical Power Analysis in Research

Second Edition

February 2015 | 160 pages | SAGE Publications, Inc

With increased emphasis on helping readers understand the context in which power calculations are done, this Second Edition 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. 

1. The Rules of the Game
Exploratory Studies  
Hypothesis Formulation  
Null Hypothesis  
The Statistical Test  
Effect Sizes: Critical, True, and Estimated  
2. General Concepts
Introduction to the Power Table  
Statistical Considerations  
3. The Pivotal Case: Interclass Correlation
The Intraclass Correlation Test  
The ANOVA Approach to Intraclass Correlation Test  
Normal Approximation to the Intraclass Theory  
Non-Central t  
Variance Ratios  
4. Equality of Means: Z- and T-Test, Balanced ANOVA
Single-Sample Test, Variance Known: z-test  
Single-Sample t-test  
Two Sample t-test  
An Exercise in Planning  
Balanced Analysis of Variance (ANOVA)  
5. Correlation Coefficients
Intraclass Correlation Coefficient  
Product-Moment Correlation Coefficient  
Rank Correlation Coefficients  
You Study What You Measure!  
6. Linear Regression Analysis
Simple Linear Regression  
Experimental Design: Choosing the X-Values  
Simple Linear Moderation Example  
Problems: Collinearity and Interactions  
Multiple Linear Regression  
7. Homogeneity of Variance Tests
Two Independent Samples  
Matched Samples  
8. Binomial Tests
Single-Sample Binomial Tests  
Two-Sample Binomial Tests  
9. Contingency Table Analysis
The I X J x^2-test  
An Example of a 3 X 2 Contingency Table Analysis  
10. Wrap-Up

"Kraemer and Blasey provide an authoritative and readable introduction into applied statistical power analysis and its application with many common statistical procedures."

Glenn Gamst
University of La Verne

“This is a necessary text for anyone conducting research in the real world. Nowhere else will you find a better answer to the question, 'How Many Subjects?'” 

Bryan Rooney
Concordia University College of Alberta

Too advanced for the course; but on additional/further readings list.

Ms Susanne Kirchmair
Accounting , MCI Management Center Innsbruck
June 7, 2016
Key features


  • Power computations are now placed in the proper context as one small but crucial step in applying the scientific method.
  • The number of tests to which the methods can be applied has been extended.
  • The book now incorporates the authors’ experience where errors in design and interpretation of statistical hypothesis testing occur.
  • Recent emphasis on effect sizes rather than p-values is endorsed and emphasized throughout.
  • Recent developments in consideration of moderators and mediators are acknowledged.


  • The book provides empirical researchers with the means to quickly determine a valuable piece of information; namely, what sample size is needed for a particular study.
  • The book’s tables can be used for a variety of different common tests by modifying the relationship of the effect size, design parameters, and sample size to the row and column definitions.
  • The authors’ approach corresponds to “differential diagnosis” in medicine, in this case, shifting through various valid options available for testing a hypothesis and choosing the one most likely to succeed.

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