Doubly robust semiparametric estimation for the missing censoring indicator model |
| |
Authors: | Sundarraman Subramanian Dipankar Bandyopadhyay |
| |
Institution: | 1. Center for Applied Mathematics and Statistics, Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, NJ 07102, United States;2. Division of Biostatistics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, United States |
| |
Abstract: | 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. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|