Statistical inference for self-designing clinical trials with a one-sided hypothesis.
Statistical inference for self-designing clinical trials with a one-sided hypothesis.
复制标题
具有片面假设的自我设计临床试验的统计推断。
DOI：
10.1111/j.0006-341x.1999.00190.x
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
Fisher,L
中科院分区：
文献类型：
--
作者：
Shen,Y;Fisher,L
在监测临床试验的过程中，利用中期结果来确定当备择假设为真时，原计划的样本量是否能够提供足够的把握度，并在必要时调整样本量，这似乎很有吸引力。在本文中，我们提出了一个灵活的顺序监测方法，在Fisher（1998）的工作，其中的最大样本量不必事先指定。最终的检验统计量是基于顺序收集的数据的加权平均值构建的，其中每个阶段的权重函数由该阶段之前的观测数据确定。这样的权重函数用于保持最终检验统计量的方差的完整性，从而保持总体I类错误率。此外，当存在治疗差异时，权重函数在终止试验中起隐含作用。最后，该设计允许在有效性结果为充分阴性时提前停止试验。仿真研究证实了该方法的性能。
In the process of monitoring clinical trials, it seems appealing to use the interim findings to determine whether the sample size originally planned will provide adequate power when the alternative hypothesis is true, and to adjust the sample size if necessary. In the present paper, we propose a flexible sequential monitoring method following the work of Fisher (1998), in which the maximum sample size does not have to be specified in advance. The final test statistic is constructed based on a weighted average of the sequentially collected data, where the weight function at each stage is determined by the observed data prior to that stage. Such a weight function is used to maintain the integrity of the variance of the final test statistic so that the overall type I error rate is preserved. Moreover, the weight function plays an implicit role in termination of a trial when a treatment difference exists. Finally, the design allows the trial to be stopped early when the efficacy result is sufficiently negative. Simulation studies confirm the performance of the method.