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An Optimised Optional Randomised Response Technique

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  • Kavya Pushadapu
  • Sarjinder Singh
  • Stephen A. Sedory

Abstract

In this paper, we begin by reviewing the optional randomised response technique estimator (ORRTE) developed by Chaudhuri and Mukerjee for estimating the proportion of a sensitive characteristic in a population. We show that their estimator is unbiased and has smaller variance than the Warner's estimator. Then we make an attempt at developing an optimised optional randomised response technique estimator (OORRTE). The proposed OORRTE is shown to be more efficient than the ORRTE. Findings from simulation studies are discussed and interpreted for various situations. Sample sizes for the Warner's estimator, the ORRTE and the OORRTE are computed based on power analysis introduced by Ulrich, Schroter, Striegel and Simon. Finally, we include an application to real data on COVID‐19 by considering it to be partially sensitive variable; that is, sensitive to some but not to others. The data used are included in the paper and the R‐codes used in the simulation study are documented in online material.

Suggested Citation

  • Kavya Pushadapu & Sarjinder Singh & Stephen A. Sedory, 2025. "An Optimised Optional Randomised Response Technique," International Statistical Review, International Statistical Institute, vol. 93(1), pages 130-149, April.
    • Handle: RePEc:bla:istatr:v:93:y:2025:i:1:p:130-149
    DOI: 10.1111/insr.12581
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