Assessing Sensitive Attributes Using the Randomized Response Technique: Evidence for the Importance of Response Symmetry

Abstract

Randomized response techniques (RRTs) aim to reduce social desirability bias in the assessment of sensitive attributes but differ regarding privacy protection. The less protection a design offers, the more likely respondents cheat by disobeying the instructions. In asymmetric RRT designs, respondents can play safe by giving a response that is never associated with the sensitive attribute. Symmetric RRT designs avoid the incentive to cheat by not allowing such responses. We tested whether a symmetric variant of a cheating detection model (CDM) increases compliance with the instructions in a survey of academic dishonesty among 2,254 Chinese students. As we observed more noncompliance in the asymmetric than symmetric variant, we recommend the use of symmetric CDMs, which can easily be tested within multinomial models.