Singh et al. (2017) have developed calibration estimators of population mean in two-stage stratified random sampling by calibrating integrated sampling design weight when the auxiliary information is available at element (second stage unit) level for the entire population. Obviously, if the auxiliary information is available at the element level for entire population, then population mean/total of the auxiliary variable is also known. In the present paper, double (two-steps) calibration estimators of the population mean have been developed by calibrating integrated sampling design weight at first step and calibrating stratum weight at the second step using known population total/mean of the auxiliary variable. A limited simulation study with real data has been conducted to examine the relative performance of the calibration estimators over the usual estimator of the population mean without using auxiliary information in two-stage stratified random sampling. It has been found from the results of simulation study that double (two-steps) calibration estimator has brought considerable improvement in the precision of the estimate of population mean
