Efficient Estimation in a Two-Stage Randomized Response Model
Sally Abdelfatah and
Reda Mazloum
Mathematical Population Studies, 2015, vol. 22, issue 4, 234-251
Abstract:
A two-stage randomized response model is devised to circumvent the lack of answers to a sensitive question. Respondents who have not answered the sensitive question in the first stage are requested in the second stage to either answer the sensitive question (second attempt then) or to draw a card indicating "yes" or "no". In the latter case, they are required to report the outcome. This apparently innocent device helps to build a more efficient estimator of the proportion of the population having a given sensitive attribute. The procedure also increases the respondents' cooperation. As other estimators of the proportion of the population having a given sensitive attribute using randomized response models, this estimator can formally take values outside the unit interval, a possibility which should not be allowed. The minimum sample size for which the frequency of estimates outside [0,1] is small enough is obtained by simulation.
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/08898480.2014.953897 (text/html)
Access to full text is restricted to subscribers.
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:taf:mpopst:v:22:y:2015:i:4:p:234-251
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GMPS20
DOI: 10.1080/08898480.2014.953897
Access Statistics for this article
Mathematical Population Studies is currently edited by Prof. Noel Bonneuil, Annick Lesne, Tomasz Zadlo, Malay Ghosh and Ezio Venturino
More articles in Mathematical Population Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().