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

• Published in: Biometrics Vol. 61; no. 1; pp. 170 - 178
• Main Authors: Chen, Y. Q., Jewell, N. P., Lei, X., Cheng, S. C.
• Format: Journal Article
• Language: English
• Published: 350 Main Street , Malden , MA 02148 , U.S.A , and P.O. Box 1354, 9600 Garsington Road , Oxford OX4 2DQ , U.K Blackwell Publishing 01-03-2005; International Biometric Society; Blackwell Publishing Ltd
• 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
• ISSN: 0006-341X; 1541-0420
• DOI: 10.1111/j.0006-341X.2005.030224.x

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.