New Stratified Bayesian Estimators Using Warner’s Randomized Response Technique Through Mixed Priors

Authors

  • A. O. Adepetun c/o Department of Statistics, Federal University of Technology, PMB704, Akure, Ondo State, Nigeria.
  • A. A. Adewara c/o Department of Statistics, University of Ilorin, PMB 1515, Ilorin, Kwara State, Nigeria.

DOI:

https://doi.org/10.3329/jsr.v10i3.35174

Keywords:

Stratified Bayesian estimators, Mixed priors, Population proportion, Randomized response technique, Sensitive trait.

Abstract

In this paper, we propose new stratified Bayesian estimators of population proportion of a sensitive trait by adopting a mixture of alternative beta distributions as quantification of prior information in a stratified random sampling situation. Data were collected through Warner’s randomized response technique. To study the performance of the newly developed stratified estimators, mean squared error and absolute bias were used as performance criteria. The proposed estimators were compared with the existing one. We observed that the proposed estimators are more sensitive to responses than the existing one at various sample sizes respectively.


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Author Biographies

A. O. Adepetun, c/o Department of Statistics, Federal University of Technology, PMB704, Akure, Ondo State, Nigeria.

Department of Statistics/Lecturer I

A. A. Adewara, c/o Department of Statistics, University of Ilorin, PMB 1515, Ilorin, Kwara State, Nigeria.

Department of Statistics/Associate Professor

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Published

2018-09-01

How to Cite

Adepetun, A. O., & Adewara, A. A. (2018). New Stratified Bayesian Estimators Using Warner’s Randomized Response Technique Through Mixed Priors. Journal of Scientific Research, 10(3), 249–259. https://doi.org/10.3329/jsr.v10i3.35174

Issue

Vol. 10 No. 3 (2018)

Section

Section A: Physical and Mathematical Sciences

License

© Journal of Scientific Research

Creative Commons License

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