Semiparametric fractional imputation using empirical likelihood in survey sampling. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Chen, Sixia; Kim, Jae kwang
• Is Part Of: Statistical theory and related fields. Volume 1:Issue 1(2017)
• Page Start: 69
• Page End: 81
• Publication Date: 2017-01-02
• Subjects: Item non-response -- missing data -- quantile estimation -- robust estimation; Statistics -- Periodicals; Statistics; Periodicals; Electronic journals; 001.422
• DOI: 10.1080/24754269.2017.1328244
• Languages: English
• ISSNs: 2475-4269

Abstract

ABSTRACT: 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 item non-response 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 -consistent estimates for various parameters. Variance estimation is implemented using a jackknife method. Two limited simulation studies are presented to compare several imputation estimators.