Semiparametric fractional imputation using empirical likelihood in survey sampling

Sixia Chen and Jae kwang Kim

Statistical Theory and Related Fields, 2017, vol. 1, issue 1, 69-81

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 n$\sqrt{n}$-consistent estimates for various parameters. Variance estimation is implemented using a jackknife method. Two limited simulation studies are presented to compare several imputation estimators.

Date: 2017
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DOI: 10.1080/24754269.2017.1328244

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