WEAK-CONVERGENCE OF TIME-SEQUENTIAL CENSORED RANK STATISTICS WITH APPLICATIONS TO SEQUENTIAL TESTING IN CLINICAL-TRIALS
成果类型：
Article
署名作者：
MING, GG; TZE, LL
署名单位：
Stanford University
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
发表日期：
1991
页码：
1403-1433
关键词：
摘要：
A general weak convergence theory is developed for time-sequential censored rank statistics in the two-sample problem of comparing time to failure between two treatment groups, such as in the case of a clinical trial in which patients enter serially and, after being randomly allocated to one of two treatments, are followed until they fail or withdraw from the study or until the study is terminated. Applications of the theory to time-sequential tests based on these censored rank statistics are also discussed.