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A nonparametric test for comparing survival functions based on restricted distance correlation
被引:0
|作者:
Zhang, Qingyang
[1
]
机构:
[1] Univ Arkansas, Dept Math Sci, Fayetteville, AR 72701 USA
来源:
DEPENDENCE MODELING
|
2023年
/
11卷
/
01期
关键词:
non-proportional hazards;
restricted distance correlation;
omnibus test;
strong consistency;
D O I:
10.1515/demo-2023-0108
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
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) 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.
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