An optimal design for screening trials
An optimal design for screening trials
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DOI：
10.2307/2534011
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发表时间：
1998-03-01
期刊：
影响因子：
1.9
通讯作者：
Leung, DHY
中科院分区：
文献类型：
--
作者：
Wang, YG;Leung, DHY
Yao、Begg和利文斯顿（1996，Biometrics 52，992-1001）考虑了测试一系列潜在治疗剂的最佳组大小，以在给定错误率下尽快鉴定有希望的治疗剂。将每种药物试验的患者数量固定为组大小。我们考虑一个序贯设计，允许早期接受和拒绝，我们提供了一个最佳的策略，以尽量减少使用马尔可夫决策过程所需的样本量（患者）。最小化是在两种类型（假阳性和假阴性）的错误概率的约束下，与拉格朗日乘子对应的成本参数的两种类型的错误。数值研究表明，可以大大减少所需的病人数量。
Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.