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A test for the presence of stochastic ordering under censoring: the k-sample case

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  • Hammou El Barmi

    (The City University of New York)

Abstract

In this paper, we develop an empirical likelihood-based test for the presence of stochastic ordering under censoring in the k-sample case. The proposed test statistic is formed by taking the supremum of localized empirical likelihood ratio test statistics. Its asymptotic null distribution has a simple representation in terms of a standard Brownian motion process. Through simulations, we show that it outperforms in terms of power existing methods for the same problem at all the distributions that we consider. A real-life example is used to illustrate the applicability of this new test.

Suggested Citation

  • Hammou El Barmi, 2020. "A test for the presence of stochastic ordering under censoring: the k-sample case," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(2), pages 451-470, April.
    • Handle: RePEc:spr:aistmt:v:72:y:2020:i:2:d:10.1007_s10463-018-0694-5
    DOI: 10.1007/s10463-018-0694-5
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    References listed on IDEAS

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    1. Hsin-wen Chang & Hammou El Barmi & Ian W. McKeague, 2016. "Tests for stochastic ordering under biased sampling," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(4), pages 659-682, October.
    2. Hammou El Barmi & Hari Mukerjee, 2005. "Inferences Under a Stochastic Ordering Constraint: The k-Sample Case," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 252-261, March.
    3. El Barmi, Hammou & Johnson, Matthew, 2006. "A unified approach to testing for and against a set of linear inequality constraints in the product multinomial setting," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1894-1912, September.
    Full references (including those not matched with items on IDEAS)

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