Estimation of a rare sensitive attribute in a stratified sample using Poisson distribution

Gi Sung Lee, Daiho Uhm, Jong Min Kim

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


This study proposes the estimators for the mean and its variance of the number of respondents who possessed a rare sensitive attribute based on stratified sampling schemes (stratified sampling and stratified double sampling). This study deals with the extension of the estimation reported in Land et al. [Estimation of a rare sensitive attribute using Poisson distribution, Statistics (2011), in press. DOI: 10.1080/02331888.2010.524300] using a Poisson distribution and an unrelated question randomized response model reported in Greenberg et al. [The unrelated question randomized response model: Theoretical framework, J. Amer. Statist. Assoc. 64 (1969), 520-539]. In the stratified sampling, the estimators are proposed when the parameter of the rare unrelated attribute is known and unknown. The variances of estimators using a proportional and optimum allocation are also suggested. The proposed estimators are evaluated using a relative efficiency comparing variances of the estimators reported in Land et al. depending on the parameters and the probability of selecting a question. We showed that our proposed methods have better efficiencies than Land et al.'s randomized response model in some conditions. When the sizes of stratified populations are not given, other estimators are suggested using a stratified double sampling. For the proportional allocation, the difference between two variances in the stratified sampling and the stratified double sampling is given with the known rare unrelated attribute.

Original languageEnglish (US)
Pages (from-to)575-589
Number of pages15
Issue number3
StatePublished - Jun 2013

Bibliographical note

Funding Information:
The authors are grateful to the Editor-in-Chief, Professor Dr O. Bunke, Associate Editor and two anonymous learned referees for their valuable comments and suggestions on the original manuscript. This work was supported by Woosuk University.


  • Poisson distribution
  • rare sensitive attribute
  • rare unrelated attribute
  • stratified double sampling
  • stratified sampling


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