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Activity Number: 369
Type: Contributed
Date/Time: Wednesday, August 6, 2008 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #301929
Title: Testing the Structure of a Covariance Matrix
Author(s): Tracy Morris*+ and Mark E. Payton
Companies: University of Central Oklahoma and Oklahoma State University
Address: , , ,
Keywords: permutation test ; covariance matrix ; nonparametric test ; randomization test
Abstract:

The classical method for testing the structure of a covariance matrix involves a likelihood ratio test (LRT). These tests have many limitations, including the need for large sample sizes and the requirement of a random sample from a multivariate normal population. The LRT is also undefined for cases in which the sample size is not greater than the number of variables. There are many situations in which at least one of these conditions is violated. In such situations, permutation tests are appropriate. This research involves the development of a permutation test for the structure of a covariance matrix. Samples of various sizes, numbers of variables, and underlying covariance structures were simulated from multiple distributions. In each case, the type I error rates and power were examined.

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