ON THE DEVELOPMENT OF CALIBRATION ESTIMATOR IN THE PRESENCE OF MEASUREMENT ERROR AND NON-RESPONSE UNDER STRATIFIED SAMPLING
Abstract
This research extended the theory of calibration estimation and provides a novel developed calibration approach alternative to existing calibration estimators for estimating population mean of the study variable using auxiliary variable in stratified sampling. The principle of new developed calibration estimation under the presence of measurement error and non-response is provided and optimum weights were derived. A simulation study is conducted to compare the new developed calibration estimators' performance to that of other competing estimators under the presence of measurement error and non-response. The results show that the newly developed calibration estimators are more efficient than Hansen and Hurwitz, convectional separate different, convectional ratio, Azeem and Hanif, Zahid and Shabbir, Rajesh et al. estimators of population mean.