3. Applying The Permutation Test

  1. Phillip I. Good

Published Online: 23 FEB 2011

DOI: 10.1002/9780470937273.ch3

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) Applying The Permutation Test, in Analyzing the Large Number of Variables in Biomedical and Satellite Imagery, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470937273.ch3

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

SEARCH

Keywords:

  • categorical data;
  • permutation test;
  • single-value test statistics;
  • univariate statistics

Summary

This chapter examines a number of practical applications of the permutation method to the large arrays of data gathered in EEGs, MEGs, and microarrays. In any such application, researchers have to make several decisions: how and whether to reduce the vast of amount of data they have gathered, whether to make a series of single-variable comparisons or one multivariate comparison, if a series of single-variable comparisons, then how to control the overall error rate?, which test statistic to use, if a multivariate comparison, should they use a single-valued statistic? or an omnibus test? if a single-value statistic, should it be Hotelling’s T2, a related measure of distance, or some other summary statistic?, how to avoid confounding the effects of interest with other potential confounding variables such as gender and age, and the stage in the analysis at which the data should be permuted.

Controlled Vocabulary Terms

categorical data; permutation test; test statistic