University of Oklahoma, Oklahoma City, OK, USA
Iowa State University, Ames, IA, USA
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.
Niansheng Tang, Yuanyuan Ju. (2018) Statistical inference for nonignorable missing-data problems: a selective review. Statistical Theory and Related Fields 2:2, pages 105-133.