Doubly robust semiparametric estimation for the missing censoring indicator model

被引:2
|
作者
Subramanian, Sundarraman [1 ]
Bandyopadhyay, Dipankar [2 ]
机构
[1] New Jersey Inst Technol, Dept Math Sci, Ctr Appl Math & Stat, Newark, NJ 07102 USA
[2] Med Univ S Carolina, Div Biostat & Epidemiol, Charleston, SC 29425 USA
关键词
EFFICIENT ESTIMATION; SURVIVAL FUNCTION; LIKELIHOOD;
D O I
10.1016/j.spl.2009.12.019
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We present a semiparametric analysis of an augmented inverse probability of non-missingness weighted (AIPW) estimator of a survival function for the missing censoring indicator model. Although the estimator is asymptotically less efficient than a Dikta semiparametric estimator, its advantage is the insulation that it offers against inconsistency due to misspecification. We present theoretical and numerical comparisons of the asymptotic variances when there is no misspecification. In addition, we derive the asymptotic variance of the AIPW estimator when there is partial misspecification. We also present a numerical robustness study that confirms the superiority of the AIPW estimator when there is misspecification. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:621 / 630
页数:10
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