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Multiple imputation for the analysis of incomplete compound variables

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dc.contributor.authorCook, Richard J.
dc.contributor.authorWu, Changbao
dc.contributor.authorZhao, Jiwei
dc.date.accessioned2016-03-01T18:46:18Z
dc.date.available2016-03-01T18:46:18Z
dc.date.issued2015-06
dc.descriptionThis is the peer reviewed version of the following article: Zhao, J., Cook, R. J. and Wu, C. (2015), Multiple imputation for the analysis of incomplete compound variables. Can J Statistics, 43: 240–264. doi: 10.1002/cjs.11249, which has been published in final form at http://dx.doi.org/10.1002/cjs.11249. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving'en
dc.description.abstractIn many settings interest lies in modelling a compound variable defined as a function of two or more component variables. When one or more of the components are missing, the compound variable is not observed and a strategy for handling incomplete data is required. Analyses based on individuals with complete data are inefficient and yield potentially inconsistent estimators.We develop a multiple imputation strategy in this setting with an auxiliary model for imputing the compound variable directly, and one based on a multivariate imputation model for the component variables. Asymptotic properties of the imputation-based estimators are presented for the case in which the imputation model is correctly specified, and a shrinkage estimator is proposed to reduce the bias arising from misspecification of the imputation model. Finite sample properties of the various estimators are examined through simulations. An application to data from the Cana- dian Youth Smoking Survey involving a study of body mass index illustrates the approach.en
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada (RJC RGPIN 155849, CW RGPIN 05613); Canadian Institutes for Health Research (RJC FRN 13887)en
dc.identifier.urihttp://dx.doi.org/10.1002/cjs.11249
dc.identifier.urihttp://hdl.handle.net/10012/10292
dc.language.isoenen
dc.publisherWileyen
dc.relation.ispartofseriesThe Canadian Journal of Statistics;43(2)en
dc.subjectAsymptotic varianceen
dc.subjectcompound variableen
dc.subjectmultiple imputationen
dc.subjectrelative efficiencyen
dc.subjectshrinkage estimatoren
dc.titleMultiple imputation for the analysis of incomplete compound variablesen
dc.title.alternativeAnalysis of Incomplete Compound Variablesen
dc.typeArticleen
dcterms.bibliographicCitationZhao, J., Cook, R. J. and Wu, C. (2015), Multiple imputation for the analysis of incomplete compound variables. Can J Statistics, 43: 240–264. doi: 10.1002/cjs.11249en
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.typeOfResourceTexten

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