A bootstrap test for equality of variances
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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: η=( η_1,...,η_K+1)^T=0, where η_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 Levene test in controlling the Type I and Type II errors.
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