Use of coefficient of variation in calibration estimation of population mean in stratified sampling

Calibration approach is becoming more important in survey sampling. Calibration estimation helps in improving the estimates of population parameters by making use of auxiliary information. This paper proposes a new calibration estimator for estimating the population mean in the stratified random sampling with a set of new calibration constraints using known coefficient of variation of the auxiliary variable. The result has also been extended to the case of double sampling in stratified sampling. The proposed estimator has been compared with the estimator developed by Tracy et al. (2003) with the help of simulation study on real datasets.