This paper considers the problem of estimating the population mean of the study variable when auxiliary information is not available and proposes new calibration approach alternative to the recent existing calibration estimators for estimating population mean of the study variable using two auxiliary variables in stratified two-phase sampling. The theory of new calibration estimation is given and optimum weights are derived under two-phase sampling approach. A simulation study is carried out to performance of the proposed calibration estimator with other existing calibration estimators. The results demonstrate that the proposed calibration estimator is more efficient than other existing calibration estimators of the population mean in stratified two-phase sampling.

本文考虑了在没有辅助信息时估计研究变量总体均值的问题，并提出了一种新的校准方法来替代最新的现有校准估计器，该方法用于在分层两阶段抽样中使用两个辅助变量来估计研究变量的总体均值。 。给出了新的标定估计的理论，并在两阶段采样方法下得出了最佳权重。对拟议的校准器和其他现有校准器的性能进行了仿真研究。结果表明，在分层两阶段采样中，提出的校准估计器比总体平均值的其他现有校准估计器更有效。