Efficient estimation of the distribution of quality-adjusted survival time

Biometrics
H Zhao, A A Tsiatis

Abstract

Quality of life is an important aspect in evaluation of clinical trials of chronic diseases, such as cancer and AIDS. Quality-adjusted survival analysis is a method that combines both the quantity and quality of a patient's life into one single measure. In this paper, we discuss the efficiency of weighted estimators for the distribution of quality-adjusted survival time. Using the general representation theorem for missing data processes, we are able to derive an estimator that is more efficient than the one proposed in Zhao and Tsiatis (1997, Biometrika 84, 339-348). Simulation experiments are conducted to assess the small sample properties of this estimator and to compare it with the semiparametric efficiency bound. The value of this estimator is demonstrated from an application of the method to a data set obtained from a breast cancer clinical trial.

Citations

Oct 30, 2004·Statistics in Medicine·Andrew R WillanAndrea Manca
Aug 1, 2006·Biostatistics·Hongkun Wang, Hongwei Zhao
Sep 12, 2001·Biometrics·H Zhao, A A Tsiatis
Sep 12, 2001·Biometrics·P L Chen, P K Sen
May 29, 2004·European Journal of Gastroenterology & Hepatology·Andrew R Willan
Feb 18, 2010·Journal of the American Statistical Association·Liuquan Sun, Zhigang Zhang
Nov 24, 2004·Statistics in Medicine·Bingshu E ChenMin Zhan
Feb 20, 2009·Statistics in Medicine·Biswabrata Pradhan, Anup Dewanji
Feb 11, 2009·Statistics in Medicine·G Tunes-da-Silva, J P Klein
Mar 3, 2007·Statistics in Medicine·Lu Tian, Jie Huang
Aug 25, 2015·Biometrics·Lihui ZhaoL J Wei
Jan 17, 2003·Statistics in Medicine·Andrew R WillanD Y Lin
Feb 11, 2014·Statistics in Medicine·Xuelin HuangAbdus S Wahed
Dec 18, 2014·Statistics in Medicine·Yuan GengWenbin Lu
Jun 4, 2008·Circulation·David Oakes, Derick R Peterson
Jan 9, 2003·Statistical Methods in Medical Research·A R WillanE B Chen
Jan 1, 2017·Journal of the American Statistical Association·Yifei SunMei-Cheng Wang
Feb 23, 2021·Biometrics·Yingchao Zhong, Douglas E Schaubel

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