Calibration Based Regression Type Estimator of the Population Total under Two Stage Sampling Design

Abstract

Regression type estimators of the population total were developed using the calibration approach under the assumption that the population level auxiliary information is available at primary stage unit level under two stage sampling design. The variance and the estimator of the variance of the proposed estimators were also developed. Theoretical results obtained are demonstrated through simulation studies. Empirical results show that the proposed estimators outperforms the usual regression estimators under two stage sampling design in terms of the criteria of relative bias and relative root mean square error.