This study develops methods for evaluating a treatment effect on a time-to-event outcome in matched-pair studies. While most methods for paired right-censored outcomes allow determining an overall treatment effect over the course of follow-up, they generally lack in providing detailed insights into how the effect changes over time. To address this gap, we propose time-specific and overall tests for paired right-censored outcomes under randomization inference. We further extend our tests to matched observational studies by developing corresponding sensitivity analysis methods to take into account departures from randomization. Simulations demonstrate the robustness of our approach against various non-proportional hazards alternatives, including a crossing survival curves scenario. We demonstrate the application of our methods using a matched observational study from the Korean Longitudinal Study of Aging (KLoSA) data, focusing on the effect of social engagement on survival.

翻译：本研究针对匹配对研究中的时间-事件结局，开发了评估治疗效果的方法。尽管大多数针对配对右删失结局的方法能够确定随访期间的整体治疗效果，但它们通常无法提供关于效应随时间变化的详细见解。为弥补这一不足，我们提出了随机化推断框架下针对配对右删失结局的时间特异性检验与整体检验。我们进一步将检验方法拓展至匹配观察性研究，通过开发相应的敏感性分析方法以考量对随机化假设的偏离。模拟实验表明，我们的方法对包括生存曲线交叉场景在内的各种非比例风险替代模型具有稳健性。我们通过韩国老龄化纵向研究（KLoSA）数据的匹配观察性研究案例，展示了所提方法在分析社会参与对生存影响的具体应用。