A new exact p-value approach for testing variance homogeneity

ISSN 2475-4269

CN 31-2182/O1

Xinmin Li ,

School of Mathematics and Statistics, Qingdao University, Qingdao, People’s Republic of China; Department of Statistics, George Washington University,Washington, DC, USA

Hua Liang

Department of Statistics, George Washington University,Washington, DC, USA

Pages 81-86 | Received 29 Feb. 2020, Accepted 20 Mar. 2021, Published online: 22 Apr. 2021,

Abstract
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To test variance homogeneity, various likelihood-ratio based tests such as the Bartlett’s test have been proposed. The null distributions of these tests were generally derived asymptotically or approximately. We re-examine the restrictive maximum likelihood ratio (RELR) statistic, and suggest a Monte Carlo algorithm to compute its exact null distribution, and so its p-value. It is much easier to implement than most existing methods. Simulation studies indicate that the proposed procedure is also superior to its competitors in terms of type I error and powers. We analyse an environmental dataset for an illustration.

References

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To cite this article: Juan Wang, Xinmin Li & Hua Liang (2021): A new exact p-value
approach for testing variance homogeneity, Statistical Theory and Related Fields, DOI:
10.1080/24754269.2021.1907519
To link to this article: https://doi.org/10.1080/24754269.2021.1907519

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