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Article: Estimation procedures for categorical survey data with nonignorable nonresponse

TitleEstimation procedures for categorical survey data with nonignorable nonresponse
Authors
KeywordsCallbacks
Horvitz-Thompson Estimator
Imputation
Maximum Likelihood
Prediction
Response Model
Superpopulation Model
Issue Date2001
PublisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/03610926.asp
Citation
Communications In Statistics - Theory And Methods, 2001, v. 30 n. 4, p. 643-663 How to Cite?
AbstractWe consider surveys with one or more callbacks and use a series of logistic regressions to model the probabilities of nonresponse at first contact and subsequent callbacks. These probabilities are allowed to depend on covariates as well as the categorical variable of interest and so the nonresponse mechanism is nonignorable. Explicit formulae for the score functions and information matrices are given for some important special cases to facilitate implementation of the method of scoring for obtaining maximum likelihood estimates of the model parameters. For estimating finite population quantities, we suggest the imputation and prediction approaches as alternatives to weighting adjustment. Simulation results suggest that the proposed methods work well in reducing the bias due to nonresponse. In our study, the imputation and prediction approaches perform better than weighting adjustment and they continue to perform quite well in simulations involving misspecified response models. Copyright © 2001 by Marcel Dekker, Inc.
Persistent Identifierhttp://hdl.handle.net/10722/172387
ISSN
2015 Impact Factor: 0.3
2015 SCImago Journal Rankings: 0.518
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorKuk, AYCen_US
dc.contributor.authorMak, TKen_US
dc.contributor.authorLi, WKen_US
dc.date.accessioned2012-10-30T06:22:17Z-
dc.date.available2012-10-30T06:22:17Z-
dc.date.issued2001en_US
dc.identifier.citationCommunications In Statistics - Theory And Methods, 2001, v. 30 n. 4, p. 643-663en_US
dc.identifier.issn0361-0926en_US
dc.identifier.urihttp://hdl.handle.net/10722/172387-
dc.description.abstractWe consider surveys with one or more callbacks and use a series of logistic regressions to model the probabilities of nonresponse at first contact and subsequent callbacks. These probabilities are allowed to depend on covariates as well as the categorical variable of interest and so the nonresponse mechanism is nonignorable. Explicit formulae for the score functions and information matrices are given for some important special cases to facilitate implementation of the method of scoring for obtaining maximum likelihood estimates of the model parameters. For estimating finite population quantities, we suggest the imputation and prediction approaches as alternatives to weighting adjustment. Simulation results suggest that the proposed methods work well in reducing the bias due to nonresponse. In our study, the imputation and prediction approaches perform better than weighting adjustment and they continue to perform quite well in simulations involving misspecified response models. Copyright © 2001 by Marcel Dekker, Inc.en_US
dc.languageengen_US
dc.publisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/03610926.aspen_US
dc.relation.ispartofCommunications in Statistics - Theory and Methodsen_US
dc.subjectCallbacksen_US
dc.subjectHorvitz-Thompson Estimatoren_US
dc.subjectImputationen_US
dc.subjectMaximum Likelihooden_US
dc.subjectPredictionen_US
dc.subjectResponse Modelen_US
dc.subjectSuperpopulation Modelen_US
dc.titleEstimation procedures for categorical survey data with nonignorable nonresponseen_US
dc.typeArticleen_US
dc.identifier.emailLi, WK: hrntlwk@hku.hken_US
dc.identifier.authorityLi, WK=rp00741en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1081/STA-100002142-
dc.identifier.scopuseid_2-s2.0-0034895909en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034895909&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume30en_US
dc.identifier.issue4en_US
dc.identifier.spage643en_US
dc.identifier.epage663en_US
dc.identifier.isiWOS:000170041800006-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridKuk, AYC=6701324431en_US
dc.identifier.scopusauthoridMak, TK=7401931097en_US
dc.identifier.scopusauthoridLi, WK=14015971200en_US

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