2. Permutation Tests

  1. Phillip I. Good

Published Online: 23 FEB 2011

DOI: 10.1002/9780470937273.ch2

Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

How to Cite

Good, P. I. (2011) Permutation Tests, in Analyzing the Large Number of Variables in Biomedical and Satellite Imagery, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470937273.ch2

Author Information

  1. Huntington Beach CA, USA

Publication History

  1. Published Online: 23 FEB 2011
  2. Published Print: 21 MAR 2011

ISBN Information

Print ISBN: 9780470927144

Online ISBN: 9780470937273

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Keywords:

  • contingency tables;
  • distribution-free tests;
  • k-sample comparison;
  • multiple-variable comparisons;
  • p-value;
  • permutation test;
  • permutation tests;
  • test statistic;
  • two-sample comparison

Summary

Permutation tests provide exact, distribution-free solutions for a wide variety of testing problems. This chapter considers their application in both two-sample single-variable and multivariable comparisons, in k-sample comparisons, in combining multiple single-variable tests, and in analyzing data in the form of contingency tables. Some R code is provided along with an extensive list of off-the-shelf software for use in performing these tests. In each application, the same five-step procedure is followed: determine the alternative(s) of interest, choose a test statistic, compute the value of this statistic for the observations, rearrange the sample labels among the observations, and compute the value of the test statistic for the rearranged observations.

Controlled Vocabulary Terms

non-parametric methods; p-value; permutation test; test statistic