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A jackknife-based versatile test for two-sample problems with right-censored data

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  • Yu-Mei Chang
  • Chun-Shu Chen
  • Pao-Sheng Shen

Abstract

For testing the equality of two survival functions, the weighted logrank test and the weighted Kaplan--Meier test are the two most widely used methods. Actually, each of these tests has advantages and defects against various alternatives, while we cannot specify in advance the possible types of the survival differences. Hence, how to choose a single test or combine a number of competitive tests for indicating the diversities of two survival functions without suffering a substantial loss in power is an important issue. Instead of directly using a particular test which generally performs well in some situations and poorly in others, we further consider a class of tests indexed by a weighted parameter for testing the equality of two survival functions in this paper. A delete-1 jackknife method is implemented for selecting weights such that the variance of the test is minimized. Some numerical experiments are performed under various alternatives for illustrating the superiority of the proposed method. Finally, the proposed testing procedure is applied to two real-data examples as well.

Suggested Citation

  • Yu-Mei Chang & Chun-Shu Chen & Pao-Sheng Shen, 2012. "A jackknife-based versatile test for two-sample problems with right-censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 267-277, April.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:2:p:267-277
    DOI: 10.1080/02664763.2011.584524
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    1. Song Yang & Ross Prentice, 2005. "Semiparametric analysis of short-term and long-term hazard ratios with two-sample survival data," Biometrika, Biometrika Trust, vol. 92(1), pages 1-17, March.
    2. 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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    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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