A nonparametric test for comparing survival functions based on restricted distance correlation

Zhang Qingyang ()
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Zhang Qingyang: Department of Mathematical Sciences, University of Arkansas, AR 72701, Fayetteville, United States

Dependence Modeling, 2023, vol. 11, issue 1, 15

Abstract: In this article, we propose an omnibus test for comparing two survival functions under non-proportional hazards. The test statistic is based on a product-limit estimate of the restricted distance correlation, which is closely related to the L 2 {L}_{2} distance between survival curves. The strong consistency is established under mild regularity conditions. Our simulation studies show that the new test has satisfactory power under proportional hazard and various non-proportional hazards settings including delayed treatment effect, diminishing effect, and crossing survival curves; therefore, it can be a competitive alternative to the existing omnibus tests such as Kolmogorov-Smirnov test, Cramer-von Mises test, two-stage test, and the maxCombo test based on weighted log-rank statistics. Two extensions of the new test to one-sided alternatives and a Gaussian kernel are also discussed.

Keywords: non-proportional hazards; restricted distance correlation; omnibus test; strong consistency (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:11:y:2023:i:1:p:15:n:1013

DOI: 10.1515/demo-2023-0108

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