论文标题
在小N，顺序，多次分配，随机试验中进行治疗效应估计的功率先验模型
Power prior models for treatment effect estimation in a small n, sequential, multiple assignment, randomized trial
论文作者
论文摘要
一个小的N，顺序分配，随机试验（SNSMART）是一个小样本，两阶段设计，参与者最多可以依次接受两种治疗，但第二种治疗方法取决于对第一次治疗的反应。 SNSMART感兴趣的治疗效果是第一阶段的响应率，但是可以使用两个阶段的结果来从小样本中获取更多信息。一种合并两个阶段结果的新型方法都应用了先前的模型，在这种模型中，SNSMART的第一阶段结果被视为主要数据，第二阶段结果被视为补充。我们将现有的权力先验模型应用于SNSMART数据，并且还开发了POWER先验模型的新扩展。通过模拟研究将所有方法彼此相比，并与贝叶斯关节阶段模型（BJSM）进行比较。通过比较所有提出的权力先验方法中响应率估计的偏差和效率，我们建议将Fisher的精确测试或Bhattacharyya的重叠度量应用于SNSMART，以估算SNSMART中的治疗效果，这两者的性能大多数或更好地比BJSM。我们描述了这些建议的方法是首选的情况。
A small n, sequential, multiple assignment, randomized trial (snSMART) is a small sample, two-stage design where participants receive up to two treatments sequentially, but the second treatment depends on response to the first treatment. The treatment effect of interest in an snSMART is the first-stage response rate, but outcomes from both stages can be used to obtain more information from a small sample. A novel way to incorporate the outcomes from both stages applies power prior models, in which first stage outcomes from an snSMART are regarded as the primary data and second stage outcomes are regarded as supplemental. We apply existing power prior models to snSMART data, and we also develop new extensions of power prior models. All methods are compared to each other and to the Bayesian joint stage model (BJSM) via simulation studies. By comparing the biases and the efficiency of the response rate estimates among all proposed power prior methods, we suggest application of Fisher's exact test or the Bhattacharyya's overlap measure to an snSMART to estimate the treatment effect in an snSMART, which both have performance mostly as good or better than the BJSM. We describe the situations where each of these suggested approaches is preferred.
