An Efficient Family of Estimators for the Population Mean Using Auxiliary Information in the Presence of Missing Observations

This paper deals with the estimation of population mean of study variable by using information on the auxiliary variable in the presence of non-response. We suggested an efficient family of estimators for population mean based on simple random sampling when non-response occurs on both the study variable and auxiliary variables. To the first order of approximations, the bias and the mean squared error of the proposed family have been discussed. The optimum value of the real numbers and the minimum MSE have been obtained. In addition, an empirical study is used in order to access the performance of the new estimators. The results of this study showed that the new estimators are more efficient under percent relative efficiencies (PRE) criterion as compared to Hansen and Hurwitz estimators.