On the Precision of Estimators in Sampling Surveys by Multi-Parametric Calibration Weightings

Abstract

Calibration weighting is the formulation of calibration constraints with respect to a given distance measure to obtain expression of calibration weights in order to improve the efficiency of the study variable. In this paper, the effect of multi-parametric calibration weightings on the precision of estimators of mean under the stratified random sampling is examined. The results showed that at the same optimum conditions, calibration estimators with more parametric auxiliary information are more precise and highly efficient than calibration estimators with less parametric auxiliary information.