成对比较
邦费罗尼校正
多重比较问题
数学
统计
I类和II类错误
生物识别
样本量测定
继续
集合(抽象数据类型)
计算机科学
人工智能
程序设计语言
作者
Dean Follmann,Michael A. Proschan,Nancy L. Geller
出处
期刊:Biometrics
[Oxford University Press]
日期:1994-06-01
卷期号:50 (2): 325-325
被引量:115
摘要
This paper proposes a method for monitoring multi-armed clinical trials on the basis of pairwise comparisons between arms. The set of pairwise test statistics is examined during the course of the trial in order to make decisions about hypotheses, continuation of treatment arms, and continuation of the trial. Strong control of the Type I error rate is achieved by modifying two-armed group sequential procedures of Pocock (1977, Biometrika 64, 191-199), O'Brien and Fleming (1979, Biometrics 35, 549-556), and Lan and DeMets (1983, Biometrika 70, 659-663) to multi-armed trials. In the fixed-sample situation, these methods reduce to either Dunnett's or Tukey's procedure for multiple comparisons. A simpler, more flexible approximation based on the Bonferroni inequality is suggested, as well as an analogue to a sequentially rejective procedure.
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