Estimation of the proportion of a sensitive attribute based on a two-stage randomized response model with stratified unequal probability sampling

Gi Sung Lee, Ki Hak Hong, Jong Min Kim, Chang Kyoon Sond

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

To estimate the proportion of a sensitive attribute of the population that is composed of the number of different sized clusters, we suggest a two-stage randomized response model with unequal probability sampling by using Abdelfatah et al.'s procedure [Braz. J. Probab. Stat. 27 (2013) 608- 617]. We compute the estimate of the sensitive parameter, its variance, and the variance estimator for both pps sampling and two-stage equal probability sampling. We extend our model to the case of stratified unequal probability sampling and compute them. Finally, we compare the efficiency of the two estimators, one obtained by unequal probability sampling and the other by stratified unequal probability sampling.

Original languageEnglish (US)
Pages (from-to)381-408
Number of pages28
JournalBrazilian Journal of Probability and Statistics
Volume28
Issue number3
DOIs
StatePublished - Aug 2014

Keywords

  • Randomized response model
  • Sensitive attribute
  • Stratified sampling
  • Stratified unequal probability sampling
  • Two-stage model

Fingerprint

Dive into the research topics of 'Estimation of the proportion of a sensitive attribute based on a two-stage randomized response model with stratified unequal probability sampling'. Together they form a unique fingerprint.

Cite this