要将两个或多个生存分布与间隔删失数据进行比较,已经提出了各种非参数检验。有些基于Harrington和Fleming(1991)引入的Gρ$${G}^{\\rho}$$-家族,该家族允许在危险比单调下降到1的情况下具有灵活性。然而,尚不清楚如何选择参数ρ$$\\rho$$的适当值。在这项工作中,我们提出了一种新颖的线性秩检验,用于分析从比例反转风险模型得出的间隔删失数据。我们展示了它与风险比降低的关系。此测试统计量通过绕过ρ$$\\rho$$参数的选择,提供了Gρ$${G}^{\\rho}$$的基于测试统计量的替代方法。仿真结果表明其良好的性能。关于乳腺癌和吸毒者的两项研究说明了其实际用途,并强调了如果使用其他测试会被忽视的发现。该测试易于使用标准软件实现,可用于具有间隔删失数据的各种情况,以测试两个或多个独立组之间生存分布的相等性。
To compare two or more survival distributions with interval-censored data, various nonparametric tests have been proposed. Some are based on the G ρ $$ {G}^{\\rho } $$ -family introduced by Harrington and Fleming (1991) that allows flexibility for situations in which the hazard ratio decreases monotonically to unity. However, it is unclear how to choose the appropriate value of the parameter ρ $$ \\rho $$ . In this work, we propose a novel linear rank-type test for analyzing interval-censored data that derived from a proportional reversed hazard model. We show its relationship with decreasing hazard ratio. This test statistic provides an alternative to the G ρ $$ {G}^{\\rho } $$ -based test statistics by bypassing the choice of the ρ $$ \\rho $$ parameter. Simulation results show its good behavior. Two studies on breast cancer and drug users illustrate its practical uses and highlight findings that would have been overlooked if other tests had been used. The test is easy to implement with standard software and can be used for a wide range of situations with interval-censored data to test the equality of survival distributions between two or more independent groups.