The Annals of Statistics

Weak Convergence of Time-Sequential Censored Rank Statistics with Applications to Sequential Testing in Clinical Trials

Ming Gao Gu and Tze Leung Lai

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Abstract

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.

Article information

Source
Ann. Statist., Volume 19, Number 3 (1991), 1403-1433.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176348254

Digital Object Identifier
doi:10.1214/aos/1176348254

Mathematical Reviews number (MathSciNet)
MR1126330

Zentralblatt MATH identifier
0762.62020

JSTOR
links.jstor.org

Subjects
Primary: 62L10: Sequential analysis
Secondary: 62G10: Hypothesis testing 62E20: Asymptotic distribution theory 62P10: Applications to biology and medical sciences 60F17: Functional limit theorems; invariance principles 60G44: Martingales with continuous parameter

Keywords
Time-sequential censored data rank statistics martingales empirical processes maximal inequalities weak convergence sequential tests clinical trials

Citation

Gu, Ming Gao; Lai, Tze Leung. Weak Convergence of Time-Sequential Censored Rank Statistics with Applications to Sequential Testing in Clinical Trials. Ann. Statist. 19 (1991), no. 3, 1403--1433. doi:10.1214/aos/1176348254. https://projecteuclid.org/euclid.aos/1176348254


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