Improved Estimation of Sensitive Mean Using Hybrid of Partial and Optional Scrambling in the Presence of Non-Sensitive Auxiliary Information

Abstract

This article is about studying ratio, product and regression methods for estimating sensitive mean using a two-stage optional randomized response model by Gupta et al. (2010) and information on non-sensitive auxiliary variable. In particular, the additive randomized response model is used to further enhance the efficiency of the ratio, product and regression estimators (Gupta et al., 2010). We compare our proposed auxiliary information based two-stage optional randomized response estimator with recently proposed auxiliary information-based estimators. Through algebraic comparisons, it is shown that the proposed ratio, product and regression estimators are better than the corresponding estimators proposed in some recent studies. The results are also supported by a numerical study.