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Empirical likelihood based detection procedure for change point in mean residual life functions under random censorship
Author(s) -
Chen YingJu,
Ning Wei,
Gupta Arjun K.
Publication year - 2016
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.1744
Subject(s) - residual , survival function , statistics , function (biology) , empirical likelihood , econometrics , censorship , point (geometry) , empirical research , replication (statistics) , computer science , mathematics , survival analysis , algorithm , law , geometry , evolutionary biology , political science , biology , estimator
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.