Enhanced-Efficiency Randomized Response Model: A Simplified Framework

  • Ahmad M. Aboalkhair Department of Applied Statistics and Insurance, Faculty of Commerce, Mansoura University, Egypt; Department of Quantitative Methods, College of Business, King Faisal University, Saudi Arabia
  • El-Emam El-Hosseiny Department of Insurance and Risk Management, College of Business, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia
  • Mohammad A. Zayed Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia
  • Tamer Elbayoumi Department of Applied Statistics and Insurance, Faculty of Commerce, Mansoura University, Egypt; Mathematics and Statistics Department, North Carolina A\&T State University, 1601 East Market Street, Greensboro, NC 27411, USA
  • Mohamed Ibrahim Department of Applied, Mathematical \& Actuarial Statistics, Faculty of Commerce, Damietta University, Egypt; Department of Quantitative Methods, College of Business, King Faisal University, Saudi Arabia
  • A. M. Elshehawey Department of Applied, Mathematical \& Actuarial Statistics, Faculty of Commerce, Damietta University, Egypt
DOI: https://doi.org/10.19139/soic-2310-5070-2658
Keywords: Sample surveys, sensitive inquiries, randomized response technique, privacy protection, sensitive trait

Abstract

The key challenge in advancing randomized response techniques lies in enhancing efficiency while ensuring simplicity and ease of implementation. This research presents a fresh randomized response framework that achieves comparable effectiveness with fewer randomization devices, simplifying its real-world deployment. Compared to Aboalkhair’s (2025) model that depend on two randomization tools, the suggested method delivers equivalent efficiency with only a single tool. The study evaluates the new model’s superiority over existing approaches and establishes a measure of privacy protection. Through theoretical analysis and numerical comparisons, the results demonstrate distinct efficiency benefit of the suggested model.
Published
2025-07-13
How to Cite
Ahmad M. Aboalkhair, El-Hosseiny, E.-E., Mohammad A. Zayed, Tamer Elbayoumi, Mohamed Ibrahim, & A. M. Elshehawey. (2025). Enhanced-Efficiency Randomized Response Model: A Simplified Framework. Statistics, Optimization & Information Computing, 14(4), 1813-1820. https://doi.org/10.19139/soic-2310-5070-2658
Issue
Vol 14 No 4 (2025)
Section
Research Articles
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