Mitigating lack of trust in quantitative randomized response technique models

被引:12
作者
Gupta, Sat [1 ]
Zhang, Joia [2 ]
Khalil, Sadia [3 ]
Sapra, Pujita [1 ]
机构
[1] Univ N Carolina, Dept Math & Stat, Greensboro, NC 27412 USA
[2] Univ Washington, Dept Stat, Seattle, WA 98195 USA
[3] Women Univ, Lahore Coll, Dept Stat, Lahore, Pakistan
关键词
Lack of trust in RRT; RRT models; Unified measure of efficiency and privacy; Simulation study; SENSITIVITY LEVEL; EFFICIENCY;
D O I
10.1080/03610918.2022.2082477
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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.
引用
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页码:2624 / 2632
页数:9
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