Comparing the variances or robust measures of scale of two dependent variables

The paper deals with two issues. The first is testing the hypothesis that two dependent variables have a common variance. Currently, a heteroscedastic analog of the Morgan-Pitman test appears to perform relatively well. The paper demonstrates that when the marginal distributions differ in skewness,...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 51; no. 11; pp. 6610 - 6620
Main Author Wilcox, Rand R.
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.11.2022
Taylor & Francis Ltd
Subjects
Dependent variables
Morgan-Pitman test
percenile bootstrap
robust methods
Robustness
Statistical methods
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Summary:The paper deals with two issues. The first is testing the hypothesis that two dependent variables have a common variance. Currently, a heteroscedastic analog of the Morgan-Pitman test appears to perform relatively well. The paper demonstrates that when the marginal distributions differ in skewness, this method can be highly unsatisfactory. An explanation for this poor performance is provided. The second goal is to report simulation results on a percentile bootstrap method for comparing robust measures of scale. This approach was found to perform well in simulations, including the situation where the analog of the Morgan-Pitman test performs poorly.
Bibliography:ObjectType-Article-1
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content type line 14
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2020.1807568