Sensitive proportion in ranked set sampling

PLoS One. 2021 Aug 31;16(8):e0256699. doi: 10.1371/journal.pone.0256699. eCollection 2021.

Abstract

This paper considers the concomitant-based rank set sampling (CRSS) for estimation of the sensitive proportion. It is shown that CRSS procedure provides an unbiased estimator of the population sensitive proportion, and it is always more precise than corresponding sample sensitive proportion (Warner SL (1965)) that based on simple random sampling (SRS) without increasing sampling cost. Additionally, a new estimator based on ratio method is introduced using CRSS protocol, preserving the respondent's confidentiality through a randomizing device. The numerical results of these estimators are obtained by using numerical integration technique. An application to real data is also given to support the methods.

MeSH terms

  • Humans
  • Models, Statistical
  • Random Allocation
  • Sampling Studies*
  • Statistics as Topic* / methods

Grants and funding

The authors received no specific funding for this work.