Semiparametric fractional imputation using empirical likelihood in survey sampling

Date
2017-06-01
Authors
Chen, Sixia
Kim, Jae Kwang
Kim, Jae Kwang
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Altmetrics
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Statistics
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Statistics
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 nonresponse in survey sampling. The proposed method takes the form of fractional imputation (Kim, 2011) 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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This is a manuscript of an article published as Chen, Sixia, and Jae kwang Kim. "Semiparametric fractional imputation using empirical likelihood in survey sampling." Statistical theory and related fields 1, no. 1 (2017): 69-81. doi: 10.1080/24754269.2017.1328244. Posted with permission.

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