Boos, Dennis D.; Brownie, Cavell Bootstrap methods for testing homogeneity of variances. (English) Zbl 0668.62016 Technometrics 31, No. 1, 69-82 (1989). 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. Cited in 27 Documents MSC: 62F03 Parametric hypothesis testing 62G10 Nonparametric hypothesis testing 62P30 Applications of statistics in engineering and industry; control charts Keywords:Bartlett’s test; permutation; scale parameter; Taguchi methods; variability; bootstrap methods; testing homogeneity of variances; normal- theory test statistics; asymptotic analysis; Monte Carlo sampling; resampling procedures PDF BibTeX XML Cite \textit{D. D. Boos} and \textit{C. Brownie}, Technometrics 31, No. 1, 69--82 (1989; Zbl 0668.62016) Full Text: DOI