Estimation of sensitive trait proportion using Kuk's randomized response model with auxiliary information

Different strategies have been developed in survey sampling to address the issue of missing observations and non response. Asking direct questions can be difficult in getting a real response. To get over this problem, we can utilize an indirect approach, such as the randomized response technique (RRT) which is frequently used to estimate the proportion of sensitive trait. In this work, when population level data on a non-sensitive auxiliary variable is available, we provide an enhanced class of estimators for sensitive traits. This class of estimators is based on a generalization of the well-known Kuk's estimator and a usual difference estimator proposed by Diana and Perri (2009). We verify the findings with survey information obtained from the University of Wah in Pakistan and a data set previously utilized by Zaizai (2006).