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New Randomised Response Models for Two Sensitive Characteristics: Theory and Application

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  • Daryan Naatjes
  • Stephen A. Sedory
  • Sarjinder Singh

Abstract

In this paper, we introduce two new randomised response models for estimating the prevalence of two sensitive characteristics and their overlap in a population by making use of a single deck of cards. The proposed models ensure the privacy of the respondents and also reduce the burden on the respondents as they require the random selection of only one card from a deck of cards each of which contains a pair of questions that are to be answered in order. The variance expressions of the proposed estimators are derived and matched to their Cramer–Rao lower bounds of variances. A simulation study has been carried out to compare the proposed models to each other for least protection. Lastly, a real survey application, related to the acceptability of the vaccines produced by Pfizer and Moderna is included. We had findings in Summer 2021 similar to those of the Harvard Study done in December 2021, which was based on a half‐million data values, that shows the cost effectiveness of the survey design.

Suggested Citation

  • Daryan Naatjes & Stephen A. Sedory & Sarjinder Singh, 2023. "New Randomised Response Models for Two Sensitive Characteristics: Theory and Application," International Statistical Review, International Statistical Institute, vol. 91(3), pages 511-534, December.
    • Handle: RePEc:bla:istatr:v:91:y:2023:i:3:p:511-534
    DOI: 10.1111/insr.12555
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    References listed on IDEAS

    as
    1. Oluwaseun L. Olanipekun & JuLong Zhao & Rongdong Wang & Stephen A.Sedory & Sarjinder Singh, 2023. "A Theory of Higher Order Interactions Between Sensitive Variables: Empirical Evidences and an Application to a Variety of Smoking," Sociological Methods & Research, , vol. 52(2), pages 642-763, May.
    2. Lee, Cheon-Sig & Sedory, Stephen A. & Singh, Sarjinder, 2013. "Estimating at least seven measures of qualitative variables from a single sample using randomized response technique," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 399-409.
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