New Bayesian Estimators for Randomized Response Technique

Akinola Oladiran Adepetun; Amos Adedayo Adewara

Akinola Oladiran Adepetun Department of Statistics, Federal University of Technology, PMB 704, Akure, Ondo State, Nigeria.
Amos Adedayo Adewara Department of Statistics, University of Ilorin, PMB 1515, Ilorin, Kwara State, Nigeria.

Abstract

This paper proposed new Bayesian estimators of the population proportion of a sensitive attribute when life data were collected through the administration of questionnaires on abortion on 300 matured women in some selected hospitals in the metropolis. Assuming both the Kumaraswamy (KUMA) and the generalised (GLS) beta distributions as alternative beta priors, efficiency of the proposed Bayesian estimators was established for a wide interval of the values of the population proportion (. We observed that for small, medium as well as large sample sizes, the developed Bayesian estimators were better in capturing responses from respondents than the conventional simple beta estimator proposed by Hussain and Shabbir (2009a) as approaches one.

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