File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A new non-randomized model for analysis sensitive questions with binary outcomes

TitleA new non-randomized model for analysis sensitive questions with binary outcomes
Authors
KeywordsA-optimality
Bootstrap
Constrained MLE
EM algorithm
Randomized response technique
Sensitive question
Survey sampling
Issue Date2007
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/
Citation
Statistics In Medicine, 2007, v. 26 n. 23, p. 4238-4252 How to Cite?
AbstractWe propose a new non-randomized model for assessing the association of two sensitive questions with binary outcomes. Under the new model, respondents only need to answer a non-sensitive question instead of the original two sensitive questions. As a result, it can protect a respondent's privacy, avoid the usage of any randomizing device, and be applied to both the face-to-face interview and mail questionnaire. We derive the constrained maximum likelihood estimates of the cell probabilities and the odds ratio for two binary variables associated with the sensitive questions via the EM algorithm. The corresponding standard error estimates are then obtained by bootstrap approach. A likelihood ratio test and a chi-squared test are developed for testing association between the two binary variables. We discuss the loss of information due to the introduction of the non-sensitive question, and the design of the co-operative parameters. Simulations are performed to evaluate the empirical type I error rates and powers for the two tests. In addition, a simulation is conducted to study the relationship between the probability of obtaining valid estimates and the sample size for any given cell probability vector. A real data set from an AIDS study is used to illustrate the proposed methodologies. Copyright © 2007 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/172438
ISSN
2023 Impact Factor: 1.8
2023 SCImago Journal Rankings: 1.348
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorTian, GLen_US
dc.contributor.authorYu, JWen_US
dc.contributor.authorTang, MLen_US
dc.contributor.authorGeng, Zen_US
dc.date.accessioned2012-10-30T06:22:32Z-
dc.date.available2012-10-30T06:22:32Z-
dc.date.issued2007en_US
dc.identifier.citationStatistics In Medicine, 2007, v. 26 n. 23, p. 4238-4252en_US
dc.identifier.issn0277-6715en_US
dc.identifier.urihttp://hdl.handle.net/10722/172438-
dc.description.abstractWe propose a new non-randomized model for assessing the association of two sensitive questions with binary outcomes. Under the new model, respondents only need to answer a non-sensitive question instead of the original two sensitive questions. As a result, it can protect a respondent's privacy, avoid the usage of any randomizing device, and be applied to both the face-to-face interview and mail questionnaire. We derive the constrained maximum likelihood estimates of the cell probabilities and the odds ratio for two binary variables associated with the sensitive questions via the EM algorithm. The corresponding standard error estimates are then obtained by bootstrap approach. A likelihood ratio test and a chi-squared test are developed for testing association between the two binary variables. We discuss the loss of information due to the introduction of the non-sensitive question, and the design of the co-operative parameters. Simulations are performed to evaluate the empirical type I error rates and powers for the two tests. In addition, a simulation is conducted to study the relationship between the probability of obtaining valid estimates and the sample size for any given cell probability vector. A real data set from an AIDS study is used to illustrate the proposed methodologies. Copyright © 2007 John Wiley & Sons, Ltd.en_US
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/en_US
dc.relation.ispartofStatistics in Medicineen_US
dc.subjectA-optimality-
dc.subjectBootstrap-
dc.subjectConstrained MLE-
dc.subjectEM algorithm-
dc.subjectRandomized response technique-
dc.subjectSensitive question-
dc.subjectSurvey sampling-
dc.subject.meshData Interpretation, Statisticalen_US
dc.subject.meshInterviews As Topicen_US
dc.subject.meshLikelihood Functionsen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshQuestionnairesen_US
dc.subject.meshUnited Statesen_US
dc.titleA new non-randomized model for analysis sensitive questions with binary outcomesen_US
dc.typeArticleen_US
dc.identifier.emailTian, GL: gltian@hku.hken_US
dc.identifier.authorityTian, GL=rp00789en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1002/sim.2863en_US
dc.identifier.pmid17351882-
dc.identifier.scopuseid_2-s2.0-34548711356en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34548711356&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume26en_US
dc.identifier.issue23en_US
dc.identifier.spage4238en_US
dc.identifier.epage4252en_US
dc.identifier.isiWOS:000249463900002-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridTian, GL=25621549400en_US
dc.identifier.scopusauthoridYu, JW=16204381100en_US
dc.identifier.scopusauthoridTang, ML=7401974011en_US
dc.identifier.scopusauthoridGeng, Z=7101959654en_US
dc.identifier.issnl0277-6715-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats