Abstract
In this paper we are concerned with the problem of testing against the simple-tree alternative that there is at least one treatment more effective than the control when data are subject to random right-censorship. A class of tests based on linear combinations of two-sample weighted logrank statistics each comparing an individual treatment with the control is proposed. Asymptotic relative efficiencies of the simple-tree versions of Gehan-Wilcoxon, logrank and Peto-Prentice-Wilcoxon under Lehmann and scale alternatives are evaluated for various combinations of survival distributions and censoring probabilities. The results of a Monte Carlo level and power study are presented. An illustrated numerical example is also reported.
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Chen, YI. Simple-Tree Weighted Logrank Tests for Right-Censored Data. Annals of the Institute of Statistical Mathematics 50, 311–324 (1998). https://doi.org/10.1023/A:1003495232676
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DOI: https://doi.org/10.1023/A:1003495232676