Identifying combined design and analysis procedures in two-stage trials with a binary end point.
Identifying combined design and analysis procedures in two-stage trials with a binary end point.
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DOI：
10.1002/sim.5468
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发表时间：
2012-12-20
影响因子：
2
通讯作者：
Wason, James
中科院分区：
文献类型：
--
作者：
Bowden, Jack;Wason, James
两阶段试验设计提供了提前停止有效性或无效性的灵活性，并且很受欢迎，因为它们的平均样本量小于具有相同I型和II型错误率的传统试验。这使得它们在经济上具有吸引力，但从长远来看，也具有减少无效治疗患者数量的伦理利益。使预期样本量最小化的设计通常被称为“最优”设计。然而，两阶段设计可能会在试验结束时对参数估计值产生实质性偏倚。在本文中，我们认为，在决定两阶段试验设计时，还应考虑所选估计方法的预期性能。我们回顾了标准和偏差调整的最大似然估计以及平均和中位数无偏估计的性质。然后，我们确定最佳的两阶段设计和分析程序，平衡预计样本量的考虑与估计性能。我们提供软件来实现这种新方法。版权所有© 2012约翰威利父子有限公司.
Two-stage trial designs provide the flexibility to stop early for efficacy or futility and are popular because they have a smaller sample size on average than a traditional trial has with the same type I and II error rates. This makes them financially attractive but also has the ethical benefit of reducing, in the long run, the number of patients who are given ineffective treatments. Designs that minimise the expected sample size are often referred to as ‘optimal’. However, two-stage designs can impart a substantial bias into the parameter estimate at the end of the trial. In this paper, we argue that the expected performance of one's chosen estimation method should also be considered when deciding on a two-stage trial design. We review the properties of standard and bias-adjusted maximum likelihood estimators as well as mean and median unbiased estimators. We then identify optimal two-stage design and analysis procedures that balance projected sample size considerations with those of estimator performance. We make available software to implement this new methodology. Copyright © 2012 John Wiley & Sons, Ltd.
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