New Bayesian Estimators for Randomized Response Technique
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Date
2017
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Publisher
Malaysian Journal of Applied Sciences
Abstract
This paper proposes 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 Akure, Ondo State, Nigeria. 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 (π). 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 π approaches one.
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Keywords
Alternative beta priors; sensitive attribute; mean square error; absolute bias; efficiency.