title: Nonparametric comparison of survival functions based on interval-censored data with unequal censoring.
abstract: 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.
authors.affiliation: School of Mathematics and Statistics, Wuhan University, Wuhan, China.
authors.forename: Yanqin
authors.identifier: 0000-0002-5916-6801
authors.initials: Y
authors.lastname: Feng
authors.affiliation: Eli Lilly and Company.
authors.forename: Ran
authors.initials: R
authors.lastname: Duan
authors.affiliation: Department of Statistics, University of Missouri.
authors.forename: Jianguo
authors.identifier: 0000-0002-6946-671X
authors.initials: J
authors.lastname: Sun
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D018709:Statistics, Nonparametric; D016019:Survival Analysis
keywords: asymptotic distribution; interval-censored; nonparametric test