A Class of Ratio Estimators for Estimating Population Mean Using a Transformed Auxiliary Variable Under Stratified Random Sampling

The transformation technique can assist in improving the efficiency of the estimators in terms of bias and mean square error reduction. A class of ratio estimators for estimating population mean utilizing the transformation of an auxiliary variable has been proposed under stratified random sampling. The bias and mean square error of the proposed estimators up to the first order of approximation are obtained. Simulation studies and an application to rubber data in Thailand are investigated to compare the performance of the proposed class of estimators with existing estimators, the results show that the proposed class of estimators performs much better than other existing estimators under given conditions.