How Many Subjects?

Statistical Power Analysis in Research
2. Auflage 2015
ISBN: 978-1-4833-1954-4
Verlag: Sage Publications, Inc

Buch, Englisch, 160 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 242 g

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.

Autoren/Hrsg.

Kraemer, Helena Chmura

Blasey, Christine

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Forschungsmethodik, Wissenschaftliche Ausstattung

Inhaltsverzeichnis

PREFACE
1. The Rules of the Game
Exploratory Studies
Hypothesis Formulation
Null Hypothesis
Design
The Statistical Test
Effect Sizes: Critical, True, and Estimated
Power
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
Conclusion
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
Introduction
The I X J x^2-test
An Example of a 3 X 2 Contingency Table Analysis
10. Wrap-Up

Über Autor(innen)

Blasey, Christine
Christine Blasey is a professor in the PGSP-Stanford Consortium, an academic program taught by faculty drawn from Palo Alto University and the Stanford University School of Medicine Department of Psychiatry.

Kraemer, Helena Chmura
Helena Chmura Kraemer is professor emerita of biostatistics in the Department of Psychiatry and Behavioral Sciences at Stanford University. She earned her BA in mathematics from Smith College, attended Manchester University on a Fulbright Scholarship, and received her PhD in statistics from Stanford University. Kraemer’s specific research interests include improvement to randomized clinical trial methodology, assessment of reliability and validity of diagnoses and clinical measurement, and developing mathematical models for specific problems in behavioral and clinical research. She has published extensively in the behavioral as well as statistical literature. Kraemer has received the Harvard Prize in Psychiatric Biostatistics and Epidemiology (2001), the Andrew C. Leon Distinguished Career Award (2014), an Honorary Doctor of Science from Wesleyan University (2014), and is a member of the Institute of Medicine, National Academy of Sciences (2003). In retirement, she continues to serve on several editorial boards, and consult on research projects.