title: Empirical likelihood based detection procedure for change point in mean residual life functions under random censorship.
abstract: The mean residual life (MRL) function is one of the basic parameters of interest in survival analysis that describes the expected remaining time of an individual after a certain age. The study of changes in the MRL function is practical and interesting because it may help us to identify some factors such as age and gender that may influence the remaining lifetimes of patients after receiving a certain surgery. In this paper, we propose a detection procedure based on the empirical likelihood for the changes in MRL functions with right censored data. Two real examples are also given: Veterans' administration lung cancer study and Stanford heart transplant to illustrate the detecting procedure. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Information Systems, Analytics, Miami University, Oxford, OH, 45056, USA.
authors.forename: Ying-Ju
authors.initials: YJ
authors.lastname: Chen
authors.affiliation: Department of Mathematics Statistics, Bowling Green State University, Bowling Green, OH, 43403, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Ning
authors.affiliation: Department of Mathematics Statistics, Bowling Green State University, Bowling Green, OH, 43403, USA.
authors.forename: Arjun K
authors.initials: AK
authors.lastname: Gupta
mesh_terms: D000367:Age Factors; D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D012737:Sex Factors; D016019:Survival Analysis; D013997:Time Factors
keywords: change point; empirical likelihood; mean residual life; right censored data