Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

2019 ◽  
Vol 89 (17) ◽  
pp. 3196-3212
Author(s):  
Yunquan Song ◽  
Yanji Zhu ◽  
Xiuli Wang ◽  
Lu Lin
Keyword(s):  
Missing Data ◽  
Estimating Equations ◽  
Robust Inference

Semiparametric inverse propensity weighting for nonignorable missing data

Biometrika ◽  
2016 ◽  
Vol 103 (1) ◽  
pp. 175-187 ◽  
Author(s):  
Jun Shao ◽  
Lei Wang
Keyword(s):  
Missing Data ◽  
Missing Values ◽  
Generalized Method Of Moments ◽  
Estimating Equations ◽  
Real Data ◽  
Population Parameters ◽  
Finite Sample ◽  
External Data ◽  
Nonignorable Missing ◽  
Inverse Propensity Weighting

Abstract To estimate unknown population parameters based on data having nonignorable missing values with a semiparametric exponential tilting propensity, Kim & Yu (2011) assumed that the tilting parameter is known or can be estimated from external data, in order to avoid the identifiability issue. To remove this serious limitation on the methodology, we use an instrument, i.e., a covariate related to the study variable but unrelated to the missing data propensity, to construct some estimating equations. Because these estimating equations are semiparametric, we profile the nonparametric component using a kernel-type estimator and then estimate the tilting parameter based on the profiled estimating equations and the generalized method of moments. Once the tilting parameter is estimated, so is the propensity, and then other population parameters can be estimated using the inverse propensity weighting approach. Consistency and asymptotic normality of the proposed estimators are established. The finite-sample performance of the estimators is studied through simulation, and a real-data example is also presented.

The AU algorithm for estimating equations in the presence of missing data

2010 ◽  
Vol 80 (7-8) ◽  
pp. 639-647 ◽  
Author(s):  
Huixiu Zhao ◽  
Wen-Qing Ma ◽  
Jianhua Guo
Keyword(s):  
Missing Data ◽  
Estimating Equations

Estimating Equations Inference With Missing Data

2008 ◽  
Vol 103 (483) ◽  
pp. 1187-1199 ◽  
Author(s):  
Yong Zhou ◽  
Alan T. K Wan ◽  
Xiaojing Wang
Keyword(s):  
Missing Data ◽  
Estimating Equations
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