A Two-Stage Unrelated Question Randomized Response Model for Estimating the Prevalence of Stigmatized Attribute

Abstract

The randomized response technique (RRT) is an effective method designed to obtain the stigmatized information from respondents while assuring the privacy. In this study, we propose a new two-stage unrelated question RRT model to estimate the prevalence of sensitive attribute π when the proportion of unrelated innocuous attribute is known and unknown. A simulation study is carried out to validate the theoretical results of proposed estimators. The utility of proposed two-stage unrelated question RRT model under stratification is also explored. An efficiency comparison between the proposed two-stage unrelated question RRT model and the Singh and Suman RRT model is carried out numerically under simple and stratified random sampling.