Empirical likelihood based detection procedure for change point in mean residual life functions under random censorship |
| |
Authors: | Ying‐Ju Chen Wei Ning Arjun K. Gupta |
| |
Affiliation: | 1. Department of Information Systems, Analytics, Miami University, Oxford, OH, USA;2. Department of Mathematics Statistics, Bowling Green State University, Bowling Green, OH, USA |
| |
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. |
| |
Keywords: | change point mean residual life right censored data empirical likelihood |
|
|