A propensity score adjustment method for regression models with nonignorable missing covariates-Reference-Cited by-同舟云学术

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A propensity score adjustment method for regression models with nonignorable missing covariates

Published:2016-02 Issue: Volume:94 Page:98-119
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Jiang Depeng,Zhao Puying^ORCID,Tang Niansheng

Funder

National Science Fund for Distinguished Young Scholars of China

Research Fund for the Doctoral Program of Higher Education of China

National Nature Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference30 articles.

1. Efficient robust regression via two-stage generalized empirical likelihood;Bondell;J. Amer. Statist. Assoc.,2013

2. MICE: Multivariate imputation by chained equations in R;Buuren;J. Stat. Softw.,2011

3. Using calibration weighting to adjust for nonresponse under a plausible model;Chang;Biometrika,2008

4. Large sample properties of generalized method of moments estimators;Hansen;Econometrica,1982

5. Quantile regression via an MM algorithm;Hunter;J. Comput. Graph. Statist.,2000

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