Semiparametric Estimation of Proportional Mean Residual Life Model in Presence of Censoring

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 ce...

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Bibliographic Details
Published in:Biometrics 2005-03, Vol.61 (1), p.170-178
Main Authors: Chen, Y. Q., Jewell, N. P., Lei, X., Cheng, S. C.
Format: Article
Language:English
Subjects:
Antineoplastic Agents - therapeutic use
Biometrics
Biometry
Censorship
Chemotherapy
Clinical trial
Clinical trials
Clinical Trials as Topic - methods
Counting process
Estimation bias
Estimators
Humans
Inverse probability of censoring weighting
Life expectancy
Lung neoplasms
Lung Neoplasms - drug therapy
Lung Neoplasms - mortality
Lung Neoplasms - radiotherapy
Models, Statistical
P values
Proportional Hazards Models
Reliability functions
Residual life
Residual neoplasm
Semiparametric model
Survival Analysis
Time
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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.
ISSN:0006-341X
1541-0420
DOI:10.1111/j.0006-341X.2005.030224.x