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A pretest for using logrank or Wilcoxon in the two-sample problem

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  • Darilay, Annie Tordilla
  • Naranjo, Joshua D.

Abstract

In a two-sample location-scale model with censored data, the logrank test is asymptotically efficient when the error distribution is extreme minimum value. On the other hand, the Wilcoxon test is asymptotically efficient when the error distribution is logistic. We propose a pretest for choosing between logrank and Wilcoxon by determining if the error distribution is closer to extreme minimum value or logistic. This adaptive test is compared with the logrank and Wilcoxon tests through simulation.

Suggested Citation

  • Darilay, Annie Tordilla & Naranjo, Joshua D., 2011. "A pretest for using logrank or Wilcoxon in the two-sample problem," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2400-2409, July.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:7:p:2400-2409
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    References listed on IDEAS

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    1. R.D. Gill, 1980. "Censoring and Stochastic Integrals," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 34(2), pages 124-124, June.
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    Cited by:

    1. Grzegorz Wyłupek, 2021. "A permutation test for the two-sample right-censored model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(5), pages 1037-1061, October.

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