A Regression Type Estimator For Mean Estimation Under Ranked Set Sampling Alongside The Sensitivity Issue

Abstract

Koyuncu and Kadilar [7] introduced a family of estimators under simple random sampling. In this article; we adapt these estimators for ranked set sampling. Further, we suggest a regression-type estimator of population mean utilizing available supplementary information under ranked set sampling scheme alongside the sensitivity issue when the variate of interest is sensitive. The bias and mean square error of the suggested estimator is determined theoretically for both situations. A simulation study has been done to demonstrate the percentage relative efficiency of proposed estimators over the adapted and reviewed estimators.