Regression Estimator Based on Two Auxiliary Variables Under Ranked Set Sampling and Median Ranked Set Sampling in the Presence of Non-Response

Non-response is one of the major issues frequently encountered in applied research, and it significantly impairs the reliable estimation of population parameters. In this study, regression estimators utilizing information from two auxiliary variables are proposed under Ranked Set Sampling and Median Ranked Set Sampling methods in the presence of non-response. A comprehensive simulation study was conducted to evaluate the efficiency of the proposed estimators. In addition, the applicability of these estimators was demonstrated through a real data application. Based on the evaluation results, the proposed estimators demonstrated higher efficiency than the conventional regression and ratio estimators.