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Mitigating lack of trust in quantitative randomized response technique models.

Authors :
Gupta, Sat
Zhang, Joia
Khalil, Sadia
Sapra, Pujita
Source :
Communications in Statistics: Simulation & Computation. 2024, Vol. 53 Issue 6, p2624-2632. 9p.
Publication Year :
2024

Abstract

Social Desirability Bias (SDB) often leads to low response rate or worse, untruthful responding during face-to-face surveys involving sensitive questions. Randomized Response Technique (RRT) is often used to circumvent SDB by allowing respondents to provide a scrambled response. However, if respondents do not trust the RRT model, significant bias can still be introduced in the estimates. Yet, none of the quantitative RRT models currently account for respondents' lack of trust. We propose an Optional Enhanced Trust (OET) quantitative RRT model that mitigates the effect of respondents' lack of trust by allowing respondents who do not trust the traditional additive RRT model to use an alternative scrambling technique. Using a combined measure of respondent privacy and model efficiency, we demonstrate both theoretically and empirically that the proposed OET model is superior to the traditional Warner's model. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03610918
Volume :
53
Issue :
6
Database :
Academic Search Index
Journal :
Communications in Statistics: Simulation & Computation
Publication Type :
Academic Journal
Accession number :
178068600
Full Text :
https://doi.org/10.1080/03610918.2022.2082477