Sequential monitoring of randomized trials traditionally relies on parametric assumptions or asymptotic approximations. We discuss a nonparametric sequential test and its application to continuous and time-to-event endpoints that derives validity solely from the randomization mechanism. Using a betting framework, these tests constructs a test martingale by sequentially wagering on treatment assignments given observed outcomes. Under the null hypothesis of no treatment effect, the expected wealth cannot grow, guaranteeing anytime-valid Type I error control regardless of stopping rule. We prove validity and present simulation studies demonstrating calibration and power. These methods provide a conservative, assumption-free complement to model-based sequential analyses.

翻译：随机化试验的序贯监测传统上依赖于参数假设或渐近近似。本文讨论了一种非参数序贯检验方法及其在连续型终点和事件发生时间终点中的应用，其有效性完全源于随机化机制。利用博弈框架，这些检验通过根据观察到的结果序贯地对治疗分配进行"下注"来构建检验鞅。在无治疗效应的原假设下，期望"财富"不会增长，从而保证无论采用何种停止规则都能实现随时有效的第一类错误控制。我们证明了该方法的有效性，并通过模拟研究展示了其校准能力和检验功效。这些方法为基于模型的序贯分析提供了一种保守的、无假设的补充。