A Trust-Enhanced Binary RRT Model with Measurement Errors
Mahnoor Asmat, Sadia Khalil, Sat Gupta
Source abstract
Human surveys in a variety of disciplines experience challenges such as social desirability bias, confidentiality distrust by the respondents, and errors in measurement. All these factors may significantly reduce the quality of the data. To handle these challenges, a variant of the Randomized Response Technique (RRT) for binary sensitive variables has been suggested in this study. This builds on recent studies where trust enhancement has been implemented in the binary domain but not in the presence of measurement errors. This study attempts to fill that gap. Extensive simulations are used to validate theoretical results. We also highlight the risks involved in naively assuming that measurement errors do not exist.
Evidence graph
No public relationships recorded yet.
Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.