Estimating Concealment Behavior via Innovative and Effective Randomized Response Model

Estimating concealment behavior via direct questioning often fails. One proposed and effective solution to tackle this challenge is the Randomized Response Technique (RRT). This study aims to present a new efficient and easily applicable randomized response model as a practical tool for estimating concealment behavior with improved reliability. Efficiency examination and privacy protection of the proposed model are analyzed. As a real-world implementation of the model, the case of COVID-19 non-disclosure among university students is investigated as an example of concealment behavior. The proposed model, with a rational choice of parameters, was tested on a sample of university students and demonstrated practical reliability in real-world settings. Health status disclosure ratio was estimated. This estimate serves as a foundation for predicting concealment behavior in different fields.