A novel efficient randomized response model designed for attributes of utmost sensitivity
Ahmad M. Aboalkhair,
Mohammad A. Zayed,
Abdullah H. Al-Nefaie,
Mahmaod Alrawad,
A.M. Elshehawey
Affiliations
Ahmad M. Aboalkhair
Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa, 31982, Saudi Arabia; Department of Applied Statistics and Insurance, Faculty of Commerce, Mansoura University, Mansoura, 35516, Egypt; Corresponding author. Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Mohammad A. Zayed
Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa, 31982, Saudi Arabia; Department of Applied Statistics and Insurance, Faculty of Commerce, Mansoura University, Mansoura, 35516, Egypt; Corresponding author. Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Abdullah H. Al-Nefaie
Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
Mahmaod Alrawad
Department of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa, 31982, Saudi Arabia
A.M. Elshehawey
Department of Applied, Mathematical & Actuarial Statistics, Faculty of Commerce, Damietta University, New Damietta, 34519, Egypt
The existence of potential incomplete truthful reporting emerges when dealing with topics of great sensitivity. This paper introduces a novel, efficient randomized response model to address the challenges of untruthful reporting. It is meant to improve the accuracy of estimating highly sensitive attributes. The suggested model represents a modified version of Aboalkhair's model (2024) that was found to be an efficient substitute for the models developed by Warner and Mangat & Singh. This study examines the circumstances under which the suggested model outperforms alternative models in terms of efficiency. Theoretical and numerical comparisons of efficiency with alternative models, assuming incomplete truthful reporting, revealed the superior performance of the suggested model. Furthermore, a measure of privacy protection is computed.
