Bootstrap Methods for Testing Homogeneity of Variances

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Abstract
This article describes the use of bootstrap methods for the problem of testing homogeneity of variances when means are not assumed equal or known. The methods are new in this context and allow the use of normal-theory test statistics such as F = s 2 1/s 2 2 without the normality assumption that is crucial for validity of critical values obtained from the F distribution. Both asymptotic analysis and Monte Carlo sampling show that the new resampling procedures compare favorably with older methods in terms of test validity and power.

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