Estimating concealment behavior via innovative and effective randomized response model

  • 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 Mathematics, North Carolina A &T State University, 1601 E Market St, Greensboro, NC, 27411, USA
  • Mohamed Ibrahim 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-2310-5070-2522
Keywords: Concealment behavior, sample surveys, andomized response technique, privacy measure

Abstract

Estimating concealment behavior via direct questioning often fail. 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 tool for measuring concealment behavior. 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 proved to be practically reliable. Health status disclosure ratio was estimated. This estimate serves as a foundation for predicting the concealment behavior in different fields.
Published
2025-04-24
How to Cite
Ahmad M. Aboalkhair, El-Hosseiny, E.-E., Mohammad A. Zayed, Tamer Elbayoumi, Mohamed Ibrahim, & A. M. Elshehawey. (2025). Estimating concealment behavior via innovative and effective randomized response model. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-2522
Issue
Online First
Section
Research Articles
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