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A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

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  • Gi-Sung Lee
  • Ki-Hak Hong
  • Chang-Kyoon Son

Abstract

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.

Suggested Citation

  • Gi-Sung Lee & Ki-Hak Hong & Chang-Kyoon Son, 2019. "A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(7), pages 1585-1610, April.
  • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:7:p:1585-1610
    DOI: 10.1080/03610926.2018.1438625
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