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A Comparison of Methods for Estimating the Causal Effect of a Treatment in Randomized Clinical Trials Subject to Noncompliance
dc.contributor.authorLittle, Roderick J. A.en_US
dc.contributor.authorLong, Qien_US
dc.contributor.authorLin, Xihongen_US
dc.date.accessioned2010-04-01T14:45:13Z
dc.date.available2010-04-01T14:45:13Z
dc.date.issued2009-06en_US
dc.identifier.citationLittle, Roderick J.; Long, Qi; Lin, Xihong (2009). "A Comparison of Methods for Estimating the Causal Effect of a Treatment in Randomized Clinical Trials Subject to Noncompliance." Biometrics 65(2): 640-649. <http://hdl.handle.net/2027.42/65200>en_US
dc.identifier.issn0006-341Xen_US
dc.identifier.issn1541-0420en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/65200
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=18510650&dopt=citationen_US
dc.description.abstractWe consider the analysis of clinical trials that involve randomization to an active treatment ( T  = 1) or a control treatment ( T  = 0), when the active treatment is subject to all-or-nothing compliance. We compare three approaches to estimating treatment efficacy in this situation: as-treated analysis, per-protocol analysis, and instrumental variable (IV) estimation, where the treatment effect is estimated using the randomization indicator as an IV. Both model- and method-of-moment based IV estimators are considered. The assumptions underlying these estimators are assessed, standard errors and mean squared errors of the estimates are compared, and design implications of the three methods are examined. Extensions of the methods to include observed covariates are then discussed, emphasizing the role of compliance propensity methods and the contrasting role of covariates in these extensions. Methods are illustrated on data from the Women Take Pride study, an assessment of behavioral treatments for women with heart disease.en_US
dc.format.extent187933 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.otherAs-treated Analysisen_US
dc.subject.otherCausal Inferenceen_US
dc.subject.otherEfficacyen_US
dc.subject.otherInstrumental Variablesen_US
dc.subject.otherPer-protocol Analysisen_US
dc.subject.otherPrincipal Stratificationen_US
dc.subject.otherPropensity Scoresen_US
dc.titleA Comparison of Methods for Estimating the Causal Effect of a Treatment in Randomized Clinical Trials Subject to 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, University of Michigan, Ann Arbor, Michigan 48109, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Biostatistics, Emory University, Atlanta, Georgia 30322, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, U.S.A.en_US
dc.identifier.pmid18510650en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/65200/1/j.1541-0420.2008.01066.x.pdf
dc.identifier.doi10.1111/j.1541-0420.2008.01066.xen_US
dc.identifier.sourceBiometricsen_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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