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GENERALIZED METHOD OF MOMENTS FOR NONIGNORABLE MISSING DATA
Zhang, Li1,2; Lin, Cunjie3,4; Zhou, Yong5,6
2018-10-01
Source PublicationSTATISTICA SINICA
ISSN1017-0405
Volume28Issue:4Pages:2107-2124
AbstractIn this study, we consider the problem of nonignorable missingness in the framework of generalized method of moments. To model the missing propensity, a semiparametric logistic regression model is adopted and we modify this model with nonresponse instrumental variables to overcome the identifiability issue. Under the identifiability conditions, we mitigate the effects of nonignorable missing data through reformulated estimating equations imputed via a kernel regression method, then the idea of generalized method of moments is applied to estimate the parameters of interest and the tilting parameter in propensity simultaneously. Moreover, the consistency and the asymptotic normality of the proposed estimators are established and we find that the price we pay for estimating an unknown tilting parameter is an increased variance for the estimator of population parameters, that is quite acceptable in contrast with validation sample, especially for practical problems. The proposed method is evaluated through simulation studies and demonstrated on a data example.
KeywordEstimating equations exponential tilting generalized method of moments kernel regression nonignorable missing nonresponse instrument
DOI10.5705/ss.202016.0340
Language英语
Funding ProjectNational Natural Science Foundation of China (NSFC)[11601424] ; National Natural Science Foundation of China (NSFC)[11701561] ; Youth Foundation of the Ministry of Education of China[15YJC910009] ; Science Foundation of Northwest University[14NW31] ; China Postdoctoral Science Foundation[2015M580867] ; China Postdoctoral Science Foundation[2016T90940] ; MOE Project of Key Research Institute of Humanities and Social Sciences at Universities[16JJD910002] ; State Key Program of National Natural Science Foundation of China[71331006] ; State Key Program in the Major Research Plan of National Natural Science Foundation of China[91546202] ; National Center for Mathematics and Interdisciplinary Sciences (NCMIS) ; Key Laboratory of RCSDS, AMSS, CAS[2008DP173182] ; Innovative Research Team of Shanghai University of Finance and Economics[IRTSHUFE13122402]
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000450217700022
PublisherSTATISTICA SINICA
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/31713
Collection应用数学研究所
Affiliation1.Northwest Univ, Sch Econ & Management, Xian, Shaanxi, Peoples R China
2.Northwest Univ, Ctr Western China Econ Dev Res, Xian, Shaanxi, Peoples R China
3.Renmin Univ China, Ctr Appl Stat, Beijing, Peoples R China
4.Renmin Univ China, Sch Stat, Beijing, Peoples R China
5.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
6.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Li,Lin, Cunjie,Zhou, Yong. GENERALIZED METHOD OF MOMENTS FOR NONIGNORABLE MISSING DATA[J]. STATISTICA SINICA,2018,28(4):2107-2124.
APA Zhang, Li,Lin, Cunjie,&Zhou, Yong.(2018).GENERALIZED METHOD OF MOMENTS FOR NONIGNORABLE MISSING DATA.STATISTICA SINICA,28(4),2107-2124.
MLA Zhang, Li,et al."GENERALIZED METHOD OF MOMENTS FOR NONIGNORABLE MISSING DATA".STATISTICA SINICA 28.4(2018):2107-2124.
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