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Bayesian analysis of a sensitive proportion
Journal of the Korean Data & Information Science Society 2019;30:943-9
Published online July 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.4.943
© 2019 Korean Data and Information Science Society.

WonYoung Yun1 · Balgobin Nandram2 · Dal Ho Kim3

13Department of Statistics, Kyungpook National University
2Department of Mathematical Sciences, Worcester Polytechnic Institute
Correspondence to: Professor, Department of Statistics, Kyungpook National University, Daegu 41566, Korea. E-mail: dalkim@knu.ac.kr
Received June 26, 2019; Revised July 13, 2019; Accepted July 13, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Respondents tend to answer untruthfully when they are asked to response sensitive questions, as they are reluctant to expose their identity. In order to reduce the response bias that can be generated through this, Warner (1965) proposed a randomized design which uses a randomization device that conceals individual response and protects the respondent. Thereafter, various survey designs to reduce the response bias were proposed, and Bayesian estimation and simulation methods have also been studied. This study proposes an analysis method to reduce posterior standard deviations of the sensitive proportions in a survey with sensitive questions and compare the results with the existing analyzes through the simulation. In addition, this study applies the proposed analysis method to the actual survey with the sensitive questionnaires related to the organizational commitment to the experienced employees.
Keywords : Blocked Gibbs sampler, Gibbs sampler, grid method, latent variables, mirrored question design.