A Trust-Enhancing Variant of the Binary Randomized Response Technique

Building on recent studies on trust enhancement in quantitative Randomized Response Technique (RRT) models, this study introduces trust enhancement in a binary mixture RRT model. Our approach emphasizes building respondent trust alongside preserving anonymity. To support our theoretical findings, we conduct a simulation study. The overarching goal of our work is to shift the focus from merely protecting anonymity and accounting for lack of trust to actively fostering trust. Simulation results show that the proposed model has better quality, and succeeds in building respondent trust that results in more efficient estimates.