Calibration approach estimation of the population mean in stratified sampling

Calibration approach is most important in survey sampling. Calibration estimation improves the precision of the estimates of population parameters by using auxiliary information. We proposed two new calibration estimators for estimating the population mean in stratified random sampling with a set of new calibration constraints. The proposed estimator has been compared with Tracy et al. (2003) estimator with the help of simulation study. The resultant new estimators are more efficient than Tracy et al. (2003) estimator in stratified random sampling.