An Optimised Optional Randomised Response Technique
Kavya Pushadapu,
Sarjinder Singh and
Stephen A. Sedory
International Statistical Review, 2025, vol. 93, issue 1, 130-149
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.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1111/insr.12581
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:istatr:v:93:y:2025:i:1:p:130-149
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0306-7734
Access Statistics for this article
International Statistical Review is currently edited by Eugene Seneta and Kees Zeelenberg
More articles in International Statistical Review from International Statistical Institute Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().