Log rank检验所需样本量的测定:迭代非中心法

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。

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

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.