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dc.contributor.authorChristofides, Tasos C.en
dc.creatorChristofides, Tasos C.en
dc.date.accessioned2019-12-02T10:34:25Z
dc.date.available2019-12-02T10:34:25Z
dc.date.issued2015
dc.identifier.issn1574-1699
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/56630
dc.description.abstractTraditional survey techniques on human populations are expected to give poor results when the issue under investigation is sensitive or stigmatizing. Various sources of nonsampling error, in particular nonresponse and misleading answers, are serious threats to the validity of the conclusions. Indirect questioning techniques offer a remedy to this problem. Randomized response, introduced by Warner [14], has the lion's share in indirect questioning, but an alternative, the item count technique, is popular among social scientists. Although the original version introduced by Raghavarao and Federer [10], Miller [8], and Miller et al. [9] is easily understood by respondents and can be incorporated in structured questionnaires, it does not fully protect the privacy of the participants. In this paper, where our main priority will be the protection of privacy, we present a modified version of the item count technique. © 2015-IOS Press and the authors.en
dc.sourceModel Assisted Statistics and Applicationsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84947547967&doi=10.3233%2fMAS-150333&partnerID=40&md5=94804d90fc048fd9f4d0a178c85076e2
dc.subjectIndirect questioningen
dc.subjectitem count techniqueen
dc.subjectprotection of privacyen
dc.subjectrandomized responseen
dc.titleA new version of the item count techniqueen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.3233/MAS-150333
dc.description.volume10
dc.description.issue4
dc.description.startingpage289
dc.description.endingpage297
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.source.abbreviationModel Assisted Stat.Appl.en
dc.contributor.orcidChristofides, Tasos C. [0000-0001-6121-0683]
dc.gnosis.orcid0000-0001-6121-0683


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