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Semiparametric Estimation of Proportional Mean Residual Life Model in Presence of Censoring
Author(s) -
Chen Y. Q.,
Jewell N. P.,
Lei X.,
Cheng S. C.
Publication year - 2005
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2005.030224.x
Subject(s) - censoring (clinical trials) , residual , covariate , statistics , semiparametric regression , mathematics , estimation , regression , econometrics , accelerated failure time model , survival function , semiparametric model , regression analysis , survival analysis , medicine , estimator , economics , management , algorithm
Summary A mean residual life function is the average remaining life of a surviving subject, as it varies with time. The proportional mean residual life model was proposed by Oakes and Dasu (1990, Biometrika 77, 409–410) in regression analysis to study its association with related covariates in absence of censoring. In this article, we develop some semiparametric estimation procedures to take censoring into account. The proposed methodology is evaluated via simulation studies, and further applied to a clinical trial of chemotherapy in postoperative radiotherapy of lung cancer patients.