
doi: 10.1002/cjs.10069
AbstractHartley's test for homogeneity of k normal‐distribution variances is based on the ratio between the maximum sample variance and the minimum sample variance. In this paper, the author uses the same statistic to test for equivalence of k variances. Equivalence is defined in terms of the ratio between the maximum and minimum population variances, and one concludes equivalence when Hartley's ratio is small. Exact critical values for this test are obtained by using an integral expression for the power function and some theoretical results about the power function. These exact critical values are available both when sample sizes are equal and when sample sizes are unequal. One related result in the paper is that Hartley's test for homogeneity of variances is no longer unbiased when the sample sizes are unequal. The Canadian Journal of Statistics 38: 647–664; 2010 © 2010 Statistical Society of Canada
Diagnostics, and linear inference and regression, test for equal variances, ANOVA \(F\)-test, least favourable configuration, log concave, Parametric hypothesis testing, unimodal
Diagnostics, and linear inference and regression, test for equal variances, ANOVA \(F\)-test, least favourable configuration, log concave, Parametric hypothesis testing, unimodal
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