A pretest for using logrank or Wilcoxon in the two-sample problem
AbstractIn 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 55 (2011)
Issue (Month): 7 (July)
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Web page: http://www.elsevier.com/locate/csda
Survival analysis Logrank Wilcoxon Adaptive test Accelerated failure time;
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