SMART的样本量计算
Sample Size Calculations for SMARTs
摘要：
序贯多分配随机试验（SMART）被认为是估计和评价治疗方案的金标准。SMART的大小通常被设定为确保用于简单比较的足够功率，例如，两个固定治疗序列的比较。最佳治疗方案的估计是作为二次和假设生成分析的一部分进行的，对估计的最佳方案的正式评价推迟到后续试验。然而，运行后续试验来评估估计的最佳治疗方案是昂贵且耗时的;此外，如果原始试验对于估计最佳方案的效力不足，则在这样的后续试验中待评估的估计的最佳方案可能远非最佳。我们推导出SMART的样本量程序，以确保：（i）有足够的把握度将最佳治疗方案与标准治疗方案进行比较;以及（ii）估计的最佳方案在高概率的真实最佳方案的给定公差范围内。我们建立的渐近有效性所提出的程序，并证明其有限样本的性能在一系列的模拟实验。
英文摘要：
Sequential Multiple Assignment Randomized Trials (SMARTs) are considered the gold standard for estimation and evaluation of treatment regimes. SMARTs are typically sized to ensure sufficient power for a simple comparison, e.g., the comparison of two fixed treatment sequences. Estimation of an optimal treatment regime is conducted as part of a secondary and hypothesis-generating analysis with formal evaluation of the estimated optimal regime deferred to a follow-up trial. However, running a follow-up trial to evaluate an estimated optimal treatment regime is costly and time-consuming; furthermore, the estimated optimal regime that is to be evaluated in such a follow-up trial may be far from optimal if the original trial was underpowered for estimation of an optimal regime. We derive sample size procedures for a SMART that ensure: (i) sufficient power for comparing the optimal treatment regime with standard of care; and (ii) the estimated optimal regime is within a given tolerance of the true optimal regime with high-probability. We establish asymptotic validity of the proposed procedures and demonstrate their finite sample performance in a series of simulation experiments.
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