Homogeneous Imputation Under Two Phase Probability Proportional To Size Sampling

Abstract

In this paper, we consider the problem of missing complete at random (MCAR) values in two phase probability proportional to size (pps) sampling for the estimation of population mean. A class of estimators is considered by the suitable use of auxiliary information with the traditional estimators for imputing the missing values. Theoretically, bias and mean squared errors of the proposed estimators are obtained up to the first order approximation. Two numerical studies are carried out for relative comparison of the proposed estimators with mean estimator under two phase pps sampling for each situation.