Nonparametric comparison of survival functions based on interval‐censored data with unequal censoring

• Published in: Statistics in medicine Vol. 36; no. 12; pp. 1895 - 1906
• Main Authors: Feng, Yanqin, Duan, Ran, Sun, Jianguo
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 30.05.2017
• Subjects: asymptotic distribution; Biomedical research; Clinical trials; Data Interpretation, Statistical; Humans; interval‐censored; Models, Statistical; Nonparametric statistics; nonparametric test; Parameter estimation; Regression analysis; Statistics, Nonparametric; Survival Analysis; asymptotic distribution; nonparametric test; interval-censored
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.7239

Nonparametric comparison of survival functions is one of the most commonly required task in failure time studies such as clinical trials, and for this, many procedures have been developed under various situations. This paper considers a situation that often occurs in practice but has not been discussed much: the comparison based on interval‐censored data in the presence of unequal censoring. That is, one observes only interval‐censored data, and the distributions of or the mechanisms behind censoring variables may depend on treatments and thus be different for the subjects in different treatment groups. For the problem, a test procedure is developed that takes into account the difference between the distributions of the censoring variables, and the asymptotic normality of the test statistics is given. For the assessment of the performance of the procedure, a simulation study is conducted and suggests that it works well for practical situations. An illustrative example is provided. Copyright © 2017 John Wiley & Sons, Ltd.