Truncated survival data arise when the event time is observed only if it falls within a subject-specific region, known as the truncation set. Left-truncated data arise when there is delayed entry into a study, such that subjects are included only if their event time exceeds some other time. Quasi-independence of truncation and failure refers to factorization of their joint density in the observable region. Under quasi-independence, standard methods for survival data such as the Kaplan-Meier estimator and Cox regression can be applied after simple adjustments to the risk sets. Unlike the requisite assumption of independent censoring, quasi-independence can be tested, e.g., using a conditional Kendall's tau test. Current methods for testing for quasi-independence are powerful for monotone alternatives. Nonetheless, it is essential to detect any kind of deviation from quasi-independence so as not to report a biased Kaplan-Meier estimator or regression effect, which would arise from applying the simple risk set adjustment when dependence holds. Nonparametric, minimum p-value tests that are powerful against non-monotone alternatives are developed to offer protection against erroneous assumptions of quasi-independence. The use of conditional and unconditional methods of permutation for evaluation of the proposed tests are investigated in simulation studies. The proposed tests are applied to a study on the cognitive and functional decline in aging.

中文翻译：

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一般依赖截断的排列测试


仅当事件时间落在特定于受试者的区域（称为截断集）内时，才会观察到截断的生存数据。当延迟进入研究时，就会出现左截断数据，这样只有当受试者的事件时间超过其他时间时才会被纳入。截断和失效的准独立性是指它们在可观察区域中的联合密度的因式分解。在准独立条件下，对风险集进行简单调整后，可以应用生存数据的标准方法，例如 Kaplan-Meier 估计器和 Cox 回归。与独立审查的必要假设不同，可以测试准独立性，例如使用条件肯德尔tau 测试。当前测试准独立性的方法对于单调替代方案来说非常强大。尽管如此，有必要检测任何与准独立性的偏差，以免报告有偏差的 Kaplan-Meier 估计量或回归效应，这些效应是在依赖性成立时应用简单风险集调整而产生的。开发出对非单调替代方案有效的非参数最小 p 值检验，以防止准独立性的错误假设。在模拟研究中研究了使用条件和无条件排列方法来评估所提出的测试。所提出的测试适用于关于衰老过程中认知和功能下降的研究。