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dc.creatorYucel, RM
dc.date.accessioned2021-02-07T18:34:55Z
dc.date.available2021-02-07T18:34:55Z
dc.date.issued2008-07-13
dc.identifier.issn1364-503X
dc.identifier.issn1471-2962
dc.identifier.doihttp://dx.doi.org/10.34944/dspace/6072
dc.identifier.other18407897 (pubmed)
dc.identifier.urihttp://hdl.handle.net/20.500.12613/6090
dc.description.abstractMethods specifically targeting missing values in a wide spectrum of statistical analyses are now part of serious statistical thinking due to many advances in computational statistics and increased awareness among sophisticated consumers of statistics. Despite many advances in both theory and applied methods for missing data, missing-data methods in multilevel applications lack equal development. In this paper, I consider a popular inferential tool via multiple imputation in multilevel applications with missing values. I specifically consider missing values occurring arbitrarily at any level of observational units. I use Bayesian arguments for drawing multiple imputations from the underlying (posterior) predictive distribution of missing data. Multivariate extensions of well-known mixed-effects models form the basis for simulating the posterior predictive distribution, hence creating the multiple imputations. The discussion of these topics is demonstrated in an application assessing correlates to unmet need for mental health care among children with special health care needs. © 2008 The Royal Society.
dc.format.extent2389-2403
dc.language.isoen
dc.relation.haspartPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
dc.relation.isreferencedbyThe Royal Society
dc.rightsCC BY
dc.subjectmissing data
dc.subjectimputation
dc.subjectlinear mixed-effects models
dc.subjectcomplex sample surveys
dc.subjectlongitudinal designs
dc.subjectitem non-response
dc.titleMultiple imputation inference for multivariate multilevel continuous data with ignorable non-response
dc.typeArticle
dc.type.genreJournal Article
dc.relation.doi10.1098/rsta.2008.0038
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.date.updated2021-02-07T18:34:53Z
refterms.dateFOA2021-02-07T18:34:56Z


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