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Partial Randomized Response Model for Simultaneous Estimation of Means of Two Sensitive Variables

Author

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  • Ghulam Narjis
  • Javid Shabbir
  • Ronald Onyango
  • Tahir Mehmood

Abstract

In this study, a new partial randomized response model (RRM) has been proposed for estimating the population mean of two quantitative sensitive variables simultaneously. The utility of proposed model under stratification is also explored. The efficiency comparisons of the proposed model under simple and stratified random sampling are carried out numerically. A real data set was collected through direct questioning, proposed partial RRM and competitor randomized device from the students of statistics and animal sciences departments of Quaid-I-Azam University Islamabad, Pakistan. The performance of the proposed partial RRM is better than competitor RRM under simple and stratified random sampling.

Suggested Citation

  • Ghulam Narjis & Javid Shabbir & Ronald Onyango & Tahir Mehmood, 2022. "Partial Randomized Response Model for Simultaneous Estimation of Means of Two Sensitive Variables," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, August.
    • Handle: RePEc:hin:jnlmpe:6083646
    DOI: 10.1155/2022/6083646
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    Cited by:

    1. Pablo O. Juárez-Moreno & Agustín Santiago-Moreno & José M. Sautto-Vallejo & Carlos N. Bouza-Herrera, 2023. "Scrambling Reports: New Estimators for Estimating the Population Mean of Sensitive Variables," Mathematics, MDPI, vol. 11(11), pages 1-11, June.

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