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A multiple imputation strategy for sequential multiple assignment randomized trials
dc.contributor.authorShortreed, Susan M.en_US
dc.contributor.authorLaber, Ericen_US
dc.contributor.authorScott Stroup, T.en_US
dc.contributor.authorPineau, Joelleen_US
dc.contributor.authorMurphy, Susan A.en_US
dc.date.accessioned2014-10-07T16:09:23Z
dc.date.availableWITHHELD_13_MONTHSen_US
dc.date.available2014-10-07T16:09:23Z
dc.date.issued2014-10-30en_US
dc.identifier.citationShortreed, Susan M.; Laber, Eric; Scott Stroup, T.; Pineau, Joelle; Murphy, Susan A. (2014). "A multiple imputation strategy for sequential multiple assignment randomized trials." Statistics in Medicine 33(24): 4202-4214.en_US
dc.identifier.issn0277-6715en_US
dc.identifier.issn1097-0258en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/108622
dc.description.abstractSequential multiple assignment randomized trials (SMARTs) are increasingly being used to inform clinical and intervention science. In a SMART, each patient is repeatedly randomized over time. Each randomization occurs at a critical decision point in the treatment course. These critical decision points often correspond to milestones in the disease process or other changes in a patient's health status. Thus, the timing and number of randomizations may vary across patients and depend on evolving patient‐specific information. This presents unique challenges when analyzing data from a SMART in the presence of missing data. This paper presents the first comprehensive discussion of missing data issues typical of SMART studies: we describe five specific challenges and propose a flexible imputation strategy to facilitate valid statistical estimation and inference using incomplete data from a SMART. To illustrate these contributions, we consider data from the Clinical Antipsychotic Trial of Intervention and Effectiveness, one of the most well‐known SMARTs to date. Copyright © 2014 John Wiley & Sons, Ltd.en_US
dc.publisherSpringer‐Verlag, Inc.en_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherMultiple Imputationen_US
dc.subject.otherSequential Multiple Assignment Randomized Trialsen_US
dc.subject.otherMissing Dataen_US
dc.subject.otherTreatment Policiesen_US
dc.subject.otherDynamic Treatment Regimesen_US
dc.subject.otherIndividualized Treatmenten_US
dc.titleA multiple imputation strategy for sequential multiple assignment randomized trialsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbsecondlevelMedicine (General)en_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/108622/1/sim6223-sup-0001-SupInfo.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/108622/2/sim6223.pdf
dc.identifier.doi10.1002/sim.6223en_US
dc.identifier.sourceStatistics in Medicineen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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