BAYESIAN ESTIMATION OF POPULATION PROPORTION OF A STIGMATIZED ATTRIBUTE USING A FAMILY OF ALTERNATIVE BETA PRIORS

Abstract

In this study, we have developed the Bayes estimators of the population proportion of a stigmatized attribute when data were gathered through the randomized response technique (RRT) put forward by Hussain and Shabbir [9]. Using both the Kumaraswamy (KUMA) and the Generalised (GLS) beta distributions as a family of alternative beta priors, superiority of the derived Bayes estimators was established for a large interval of the values of the population proportion. We observed that for small, moderate as well as large sample sizes, the alternative Bayes estimators were better than the Bayes estimator proposed by Hussain and Shabbir [10] when a simple beta prior was used