Weak Convergence of Time-Sequential Censored Rank Statistics with Applications to Sequential Testing in Clinical Trials
Gu, Ming Gao ; Lai, Tze Leung
Ann. Statist., Tome 19 (1991) no. 1, p. 1403-1433 / Harvested from Project Euclid
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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.
Publié le : 1991-09-14
Classification:  Time-sequential censored data,  rank statistics,  martingales,  empirical processes,  maximal inequalities,  weak convergence,  sequential tests,  clinical trials,  62L10,  62G10,  62E20,  62P10,  60F17,  60G44 
@article{1176348254,
     author = {Gu, Ming Gao and Lai, Tze Leung},
     title = {Weak Convergence of Time-Sequential Censored Rank Statistics with Applications to Sequential Testing in Clinical Trials},
     journal = {Ann. Statist.},
     volume = {19},
     number = {1},
     year = {1991},
     pages = { 1403-1433},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176348254}
}

Gu, Ming Gao; Lai, Tze Leung. Weak Convergence of Time-Sequential Censored Rank Statistics with Applications to Sequential Testing in Clinical Trials. Ann. Statist., Tome 19 (1991) no. 1, pp.  1403-1433. http://gdmltest.u-ga.fr/item/1176348254/