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Semiparametric fractional imputation using empirical likelihood in survey sampling

Sixia Chen ,

University of Oklahoma, Oklahoma City, OK, USA

Jae kwang Kim

Iowa State University, Ames, IA, USA

Pages 69-81 | Received 07 Mar. 2017, Accepted 05 May. 2017, Published online: 01 Jun. 2021,
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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.

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