A bootstrap test for equality of variances

Authors:
Dexter O. Cahoy
Affiliations:
Program of Mathematics and Statistics, College of Engineering and Science, Louisiana Tech University, Ruston, LA 71272, United States
Venue:
Computational Statistics & Data Analysis
Year:
2010

Citing 2
Cited 2

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Abstract

We introduce a bootstrap procedure to test the hypothesis H"o that K+1 variances are homogeneous. The procedure uses a variance-based statistic, and is derived from a normal-theory test for equality of variances. The test equivalently expressed the hypothesis as H"o:@h=(@h"1,...,@h"K"+"1)^T=0, where @h"i's are log contrasts of the population variances. A box-type acceptance region is constructed to test the hypothesis H"o. Simulation results indicated that our method is generally superior to the Shoemaker and Levene tests, and the bootstrapped version of the Levene test in controlling the Type I and Type II errors.