Semiparametric fractional imputation using empirical likelihood in survey sampling  

作　　者：Sixia Chen Jae kwang Kim 

机构地区：[1]University of Oklahoma,Oklahoma City,OK,USA [2]Iowa State University,Ames,IA,USA

出　　处：《Statistical Theory and Related Fields》2017年第1期69-81,共13页统计理论及其应用（英文）

基　　金：National Institutes of Health;National Institute of General Medical Sciences[grant number 1 U54GM104938];Okla-homa Shared Clinical and Translational Resources;Alter-ations and Renovations;Oversight and Management Core and IDeA-CTR;NSF[grant number MMS-1324922].

摘　　要：The empirical likelihood method is a powerful tool for incorporating moment conditions in statistical inference.We propose a novel application of the empirical likelihood for handling itemnonresponse in survey sampling.The proposed method takes the form of fractional imputation but it does not require parametric model assumptions.Instead,only the first moment condition based on a regression model is assumed and the empirical likelihood method is applied to the observed residuals to get the fractional weights.The resulting semiparametric fractional imputation provides√n-consistent estimates for various parameters.Variance estimation is implemented using a jackknifemethod.Two limited simulation studies are presented to compare several imputation estimators.

关 键 词：Item non-response missing data quantile estimation robust estimation 

分 类 号：O17[理学—数学]