Work

A Trust-Enhancing Variant of the Binary Randomized Response Technique

Year: 2025

Type: article

Abstract: 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.

Source: Axioms

DOI: 10.3390/axioms14120864

Authors: Sat Gupta, Nikita Jayaraj, Mala Gupta, Pidugu Trisandhya

Institutions: University of North Carolina at Greensboro, Texas A&M University, The University of Texas at Austin, Bharati Vidyapeeth's College of Engineering, Delhi

Language: English

Topic: Survey Sampling and Estimation Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: National Science Foundation