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Permutation Statistical Methods

An Integrated Approach

  • Kenneth J. Berry
  • Paul W. Mielke, Jr.
  • Janis E. Johnston

Table of contents

  1. Front Matter
    Pages i-xx
  2. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 1-27
  3. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 29-55
  4. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 57-113
  5. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 115-215
  6. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 217-314
  7. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 315-365
  8. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 367-419
  9. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 421-443
  10. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 445-472
  11. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 473-542
  12. Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 543-584
  13. Back Matter
    Pages 585-622

About this book

Introduction

This research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size.

Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research.

This research monograph addresses a statistically-informed audience, and can also easily serve as a textbook in a graduate course in departments such as statistics, psychology, or biology. In particular, the audience for the book is teachers of statistics, practicing statisticians, applied statisticians, and quantitative graduate students in fields such as psychology, medical research, epidemiology, public health, and biology.

Keywords

Minkowski distance function exact tests moment approximation permutation methods resampling approximation statistical methods

Authors and affiliations

  • Kenneth J. Berry
    • 1
  • Paul W. Mielke, Jr.
    • 2
  • Janis E. Johnston
    • 3
  1. 1.Department of SociologyColorado State UniversityFort CollinsUSA
  2. 2.Department of StatisticsColorado State UniversityFort CollinsUSA
  3. 3.U.S. GovernmentAlexandriaUSA

Bibliographic information