Bayesian Analysis of Randomized Response Sum Score Variables

Abstract

The randomized-response (RR) technique is an effective survey method when collecting sensitive information. In this technique, a probability mechanism using randomization devices is commonly involved in answering to sensitive questions. In order to evaluate the survey at the most accurate extend, self-protection (SP) is introduced to describe the responses by participants who give the evasive answer without taking the result of the randomization device into account. In this study, we propose a Bayesian approach to modeling RR sum score variables under SP assumption. RR data from a Dutch survey on non-compliance with social security regulation in 2004 is used to demonstrate the proposed models.

On Bayesian Analysis of a General Class of Randomized Response Models In Social Surveys about Stigmatized Traits

“…Although the studies on the Bayesian analysis of RRTs have been done, yet a small quantity of texts on the Bayesian analysis of the RRTs is available. Winkler and Franklin [26], Pitz [8], Spurrier and Padgett [13], O'Hagan [3], Oh [18], Migon and Tachibana [9], Unnikrishnan and Kunte [21], Bar-Lev et al [7], Barabesi and Marcheselli [15,16], Kim et al [17], Hussain and Shabbir [32,33], Hussain et al [35] and Song and Kim [12] are the major references on the Bayesian analysis of the RRTs.…”

Improved Randomized Response Technique for Two Sensitive Attributes

“…All the respondents were made to go through the device twice for a single attribute. Other works in this regards include Arnab et al (2012), Singh and Sedory (2012), Song and Kim (2012).…”