A weighted log-rank test for comparing two survival curves

Lee Seung-Hwan () and Lee Eun-Joo ()
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Lee Seung-Hwan: Department of Mathematics, Illinois Wesleyan University, Bloomington, Illinois 61701, USA
Lee Eun-Joo: Department of Mathematics and Computational Sciences, Millikin University, Decatur, Illinois 62522, USA

Monte Carlo Methods and Applications, 2020, vol. 26, issue 3, 253-262

Abstract: This paper proposes a weighted log-rank test that maintains sensitivity to realistic alternatives of two survival curves, such as crossing curves, in the presence of heavy censoring. The new test incorporates a weight function that changes over the censoring level, increasing adaptivity and flexibility of the commonly used weighted log-rank tests. The new statistic is asymptotically normal under the null hypothesis that there is no difference in survival between two groups. The performances of the new test are evaluated via simulations under both proportional and non-proportional alternatives. We illustrate the new method with a real-world application.

Keywords: Censored data; Kaplan–Meier estimators; log-rank test; survival distributions; two-sample problem; proportional hazards (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1515/mcma-2020-2064

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