We propose a cost-effective outcome-dependent sampling design for the failure time data and develop an efficient inference procedure for data collected with this design. To account for the biased sampling scheme, we derive estimators from a weighted partial likelihood estimating equation. The proposed estimators for regression parameters are shown to be consistent and asymptotically normally distributed. A criteria that can be used to optimally implement the ODS design in practice is proposed and studied. The small sample performance of the proposed method is evaluated by simulation studies. The proposed design and inference procedure is shown to be statistically more powerful than existing alternative designs with the same sample sizes. We illustrate the proposed method with an existing real data from the Cancer Incidence and Mortality of Uranium Miners Study.

中文翻译：

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Cox 比例风险模型的结果依赖抽样设计和推断

我们为故障时间数据提出了一种具有成本效益的结果依赖抽样设计，并为使用这种设计收集的数据开发了一种有效的推理程序。为了说明有偏抽样方案，我们从加权偏似然估计方程中推导出估计量。回归参数的建议估计量显示为一致且渐近正态分布。提出并研究了可用于在实践中最佳实施 ODS 设计的标准。通过模拟研究评估了所提出方法的小样本性能。所提出的设计和推理程序在统计上比具有相同样本量的现有替代设计更强大。