More powerful logrank permutation tests for two-sample survival data
Abstract
Weighted logrank tests are a popular tool for analyzing right censored survival data from two independent samples. Each of these tests is optimal against a certain hazard alternative, for example the classical logrank test for proportional hazards. But which weight function should be used in practical applications? We address this question by a flexible combination idea leading to a testing procedure with broader power. Beside the test's asymptotic exactness and consistency its power behaviour under local alternatives is derived. All theoretical properties can be transferred to a permutation version of the test, which is even finitely exact under exchangeability and showed a better finite sample performance in our simulation study. The procedure is illustrated in a real data example.
Keywords
Cite
@article{arxiv.1807.05504,
title = {More powerful logrank permutation tests for two-sample survival data},
author = {Marc Ditzhaus and Sarah Friedrich},
journal= {arXiv preprint arXiv:1807.05504},
year = {2018}
}