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

Annie Tordilla Darilay and Joshua D. Naranjo

Computational Statistics & Data Analysis, 2011, vol. 55, issue 7, 2400-2409

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.

Keywords: Survival; analysis; Logrank; Wilcoxon; Adaptive; test; Accelerated; failure; time (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (1)

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