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Nested Markov Compliance Class Model in the Presence of Time-Varying Noncompliance

dc.contributor.authorLin, Julia Y.en_US
dc.contributor.authorTen Have, Thomas R.en_US
dc.contributor.authorElliott, Michael R.en_US
dc.date.accessioned2010-04-01T15:29:57Z
dc.date.available2010-04-01T15:29:57Z
dc.date.issued2009-06en_US
dc.identifier.citationLin, Julia Y.; Ten Have, Thomas R.; Elliott, Michael R. (2009). "Nested Markov Compliance Class Model in the Presence of Time-Varying Noncompliance." Biometrics 65(2): 505-513. <http://hdl.handle.net/2027.42/65981>en_US
dc.identifier.issn0006-341Xen_US
dc.identifier.issn1541-0420en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/65981
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=18759831&dopt=citationen_US
dc.description.abstractWe consider a Markov structure for partially unobserved time-varying compliance classes in the Imbens–Rubin (1997, The Annals of Statistics 25, 305–327) compliance model framework. The context is a longitudinal randomized intervention study where subjects are randomized once at baseline, outcomes and patient adherence are measured at multiple follow-ups, and patient adherence to their randomized treatment could vary over time. We propose a nested latent compliance class model where we use time-invariant subject-specific compliance principal strata to summarize longitudinal trends of subject-specific time-varying compliance patterns. The principal strata are formed using Markov models that relate current compliance behavior to compliance history. Treatment effects are estimated as intent-to-treat effects within the compliance principal strata.en_US
dc.format.extent157763 bytes
dc.format.extent3110 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Incen_US
dc.rights©2009 International Biometric Societyen_US
dc.subject.otherGeriatric Depressionen_US
dc.subject.otherHidden Markov Modelen_US
dc.subject.otherLatent Classen_US
dc.subject.otherLongitudinal Compliance Class Modelen_US
dc.subject.otherNoncomplianceen_US
dc.subject.otherPrincipal Stratificationen_US
dc.titleNested Markov Compliance Class Model in the Presence of Time-Varying Noncomplianceen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Biostatistics and Institute of Social Research, University of Michigan, Ann Arbor, Michigan 48109, U.S.A.en_US
dc.contributor.affiliationotherCenter for Multicultural Mental Health Research, Cambridge Health Alliance-Harvard Medical School, Somerville, Massachusetts 02143, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, U.S.A.en_US
dc.identifier.pmid18759831en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/65981/1/j.1541-0420.2008.01113.x.pdf
dc.identifier.doi10.1111/j.1541-0420.2008.01113.xen_US
dc.identifier.sourceBiometricsen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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