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

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

Research output: Contribution to journalArticle

1 Citation (Scopus)

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 languageEnglish
Pages (from-to)267-277
Number of pages11
JournalJournal of Applied Statistics
Volume39
Issue number2
DOIs
Publication statusPublished - 2012 Feb 1

Fingerprint

Two-sample Problem
Right-censored Data
Jackknife
Survival Function
Testing
Equality
Kaplan-Meier
Log-rank Test
Alternatives
Censored data
Defects
Choose
Numerical Experiment

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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

In: Journal of Applied Statistics, Vol. 39, No. 2, 01.02.2012, p. 267-277.

Research output: Contribution to journalArticle

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