Simultaneous Estimation of Mean of Sensitive Variable and Sensitivity level by using Generalized Optional Scrambling

Abstract

Randomized response technique introduces anonymity into subjects' responses hence encouraging more honest responses. In quantitative randomized response model, additive and multiplicative models have been developed to reduce bias. However, additive and multiplicative models may not be sufficient to reduce this bias so the generalized optional scrambling randomized response model proposed is able to reduce these problems. We also improved mean estimation utilizing information from a non-sensitive auxiliary variable by way of ratio and regression estimators in the proposed model.