### 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.

Original language | English |
---|---|

Pages (from-to) | 267-277 |

Number of pages | 11 |

Journal | Journal of Applied Statistics |

Volume | 39 |

Issue number | 2 |

DOIs | |

Publication status | Published - 2012 Feb 1 |

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### All Science Journal Classification (ASJC) codes

- Statistics and Probability
- Statistics, Probability and Uncertainty

### Cite this

*Journal of Applied Statistics*,

*39*(2), 267-277. https://doi.org/10.1080/02664763.2011.584524

}

*Journal of Applied Statistics*, vol. 39, no. 2, pp. 267-277. https://doi.org/10.1080/02664763.2011.584524

**A jackknife-based versatile test for two-sample problems with right-censored data.** / Chang, Yu Mei; Chen, Chun-Shu; Shen, Pao Sheng.

Research output: Contribution to journal › Article

TY - JOUR

T1 - A jackknife-based versatile test for two-sample problems with right-censored data

AU - Chang, Yu Mei

AU - Chen, Chun-Shu

AU - Shen, Pao Sheng

PY - 2012/2/1

Y1 - 2012/2/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84863388605&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84863388605&partnerID=8YFLogxK

U2 - 10.1080/02664763.2011.584524

DO - 10.1080/02664763.2011.584524

M3 - Article

AN - SCOPUS:84863388605

VL - 39

SP - 267

EP - 277

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

SN - 0266-4763

IS - 2

ER -