An Efficient Estimator to Estimate the Population Mean for a Sensitive Variable Using Dual Auxiliary Information

Randomized response technique (RRT) is designed to mitigate bias resulting from evasive responses in surveys. This article introduces a class of difference type RRT estimator for estimating finite population mean of a sensitive characteristic, leveraging information on auxiliary variables, as well as their ranks. The expressions of Bias and MSE are derived up to first order approximation for the proposed estimator. Empirical comparisons are made which demonstrate the superiority of our approach, particularly when incorporating information on the ranks of auxiliary variables. Our findings indicate that our proposed estimator outperforms existing alternatives developed for similar scenarios.