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Permutation Tests

A Practical Guide to Resampling Methods for Testing Hypotheses

  • Textbook
  • © 1994

Overview

Authors:
  1. Phillip Good

    1. Huntington Beach, USA

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Part of the book series: Springer Series in Statistics (SSS)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-x
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  2. A Wide Range of Applications

    • Phillip Good
    Pages 1-9

  3. A Simple Test

    • Phillip Good
    Pages 10-23

  4. Testing Hypotheses

    • Phillip Good
    Pages 24-43

  5. Experimental Designs

    • Phillip Good
    Pages 44-63

  6. Multivariate Analysis

    • Phillip Good
    Pages 64-77

  7. Categorical Data

    • Phillip Good
    Pages 78-93

  8. Dependence

    • Phillip Good
    Pages 94-104

  9. Clustering in Time and Space

    • Phillip Good
    Pages 105-109

  10. Coping with Disaster

    • Phillip Good
    Pages 110-123

  11. Which Statistic? Solving the Insolvable

    • Phillip Good
    Pages 124-139

  12. Which Test Should You Use?

    • Phillip Good
    Pages 140-148

  13. Publishing Your Results

    • Phillip Good
    Pages 149-152

  14. Increasing Computational Efficiency

    • Phillip Good
    Pages 153-165

  15. Theory of Permutation Tests

    • Phillip Good
    Pages 166-179

  16. Back Matter

    Pages 180-227
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Keywords

About this book

Permutation tests permit us to choose the test statistic best suited to the task at hand. This freedom of choice opens up a thousand practical applications, including many which are beyond the reach of conventional parametric sta­ tistics. Flexible, robust in the face of missing data and violations of assump­ tions, the permutation test is among the most powerful of statistical proce­ dures. Through sample size reduction, permutation tests can reduce the costs of experiments and surveys. This text on the application of permutation tests in biology, medicine, science, and engineering may be used as a step-by-step self-guiding reference manual by research workers and as an intermediate text for undergraduates and graduates in statistics and the applied sciences with a first course in statistics and probability under their belts. Research workers in the applied sciences are advised to read through Chapters 1 and 2 once quickly before proceeding to Chapters 3 through 8 which cover the principal applications they are likely to encounter in practice. Chapter 9 is a must for the practitioner, with advice for coping with real­ life emergencies such as missing or censored data, after-the-fact covariates, and outliers. Chapter 10 uses practical applications in archeology, biology, climatology, education and social science to show the research worker how to develop new permutation statistics to meet the needs of specific applications. The practitioner will find Chapter 10 a source of inspiration as well as a practical guide to the development of new and novel statistics.

Authors and Affiliations

  • Huntington Beach, USA

    Phillip Good

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