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  • © 2016

Permutation Statistical Methods

An Integrated Approach

  • Presents a methodological umbrella under which (1) disparate statistical methods are synthesized and integrated and (2) a number of new permutation statistical methods are developed
  • Synthesizes and integrates a large number of existing classical statistics under a common mathematical function
  • Provides computing algorithms for calculating permutation tests, and details the history of permutation statistical methods

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xx
  2. Introduction

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 1-27
  3. Completely Randomized Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 29-55
  4. Randomized Designs: Interval Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 57-113
  5. Regression Analysis of Interval Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 115-215
  6. Randomized Designs: Ordinal Data, I

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 217-314
  7. Randomized Designs: Ordinal Data, II

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 315-365
  8. Randomized Designs: Nominal Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 367-419
  9. Randomized Block Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 421-443
  10. Randomized Block Designs: Interval Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 445-472
  11. Randomized Block Designs: Ordinal Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 473-542
  12. Randomized Block Designs: Nominal Data

    • Kenneth J. Berry, Paul W. Mielke Jr., Janis E. Johnston
    Pages 543-584
  13. Back Matter

    Pages 585-622

About this book

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.

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Reviews

“This book summarizes the applications of the MRPP done by the authors to various statistical problems … . This book may be useful for researchers who are interested in extending the MRPP to other types of data and statistical problems, for example, survival data with possible censoring of observations.” (Dongsheng Tu, zbMATH 1358.62011, 2017)

Authors and Affiliations

  • Department of Sociology, Colorado State University, Fort Collins, USA

    Kenneth J. Berry

  • Department of Statistics, Colorado State University, Fort Collins, USA

    Paul W. Mielke, Jr.

  • U.S. Government, Alexandria, USA

    Janis E. Johnston

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access