SEQUENTIAL MONITORING WITH CONDITIONAL RANDOMIZATION TESTS

• 成果类型: Article
• 署名作者: Plamadeala, Victoria; Rosenberger, William F.
• 署名单位: George Mason University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/11-AOS941
• 发表日期: 2012
• 页码: 30-44
• 关键词: clinical-trials; inference; designs; rules

摘要

Sequential monitoring in clinical trials is often employed to allow for early stopping and other interim decisions, while maintaining the type I error rate. However, sequential monitoring is typically described only in the context of a population model. We describe a computational method to implement sequential monitoring in a randomization-based context. In particular, we discuss a new technique for the computation of approximate conditional tests following restricted randomization procedures and then apply this technique to approximate the joint distribution of sequentially computed conditional randomization tests. We also describe the computation of a randomization-based analog of the information fraction. We apply these techniques to a restricted randomization procedure, Efron's [Biometrika 58 (1971) 403-417] biased coin design. These techniques require derivation of certain conditional probabilities;and conditional covariances of the randomization procedure. We employ combinatoric techniques to derive these for the biased coin design.