Log rank检验所需样本量的测定:迭代非中心法

The Sample Size Determination in Log Rank Test:the Iterative Non-Central Procedure

目的:提出一种迭代非中心法,用于Log rank检验所需样本量的测定,并同Lachin-Foukes法进行了比较。方法:预置样本量重复抽样,计算Log rank检验统计量及其平均值。调整预置样本量重复操作,当该平均值充分逼近预定非中心参数时,最后预置样本量被看成是所需样本量。结果:该法所得样本量因生存分布而异,可满足Log rank检验预定功效。相比之下,Lachin-Foukes法所得样本量偏小,用于Log rank检验功效不足。结论:迭代非中心法优于Lachin-Foukes法,可用于慢性病和癌症生存研究的设计。

Objective：This paper proposes an iterative non-central procedure for the sample size determination in log rank test and compares it with the Lachin-Foulkes procedure. Methods： Samplings are performed with a prescribed size. The statistics of log rank test and their average are calculated. Such a course is repeated with adjusted sample sizes. When the average is converged to the interested value of non-central parameter, the last adjusted sample size is regarded as the required one. Results： The sample sizes determined by this procedure vary from distribution to distribution and are met with the prescribed power of log rank test. By contrast, the sample sizes from Lachin-Foulkes procedure are biased to small and unable to meet with the power. Conclusion： The iterative non-central procedure is superior to the Lachin-Foulles procedure and can be applied in planning survival studies on chronic diseases and cancer.