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Article: Adaptive design and estimation in randomized clinical trials with correlated observations

TitleAdaptive design and estimation in randomized clinical trials with correlated observations
Authors
KeywordsCorrelated data
Generalized estimating equation
Hypothesis testing
Power
Sample size
Self-designing trial
Issue Date2005
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM
Citation
Biometrics, 2005, v. 61 n. 2, p. 362-369+648 How to Cite?
AbstractClinical trial designs involving correlated data often arise in biomedical research. The intracluster correlation needs to be taken into account to ensure the validity of sample size and power calculations. In contrast to the fixed-sample designs, we propose a flexible trial design with adaptive monitoring and inference procedures. The total sample size is not predetermined, but adaptively reestimated using observed data via a systematic mechanism. The final inference is based on a weighted average of the block-wise test statistics using generalized estimating equations, where the weight for each block depends on cumulated data from the ongoing trial. When there are no significant treatment effects, the devised stopping rule allows for early termination of the trial and acceptance of the null hypothesis. The proposed design updates information regarding both the effect size and within-cluster correlation based on the cumulated data in order to achieve a desired power. Estimation of the parameter of interest and its confidence interval are proposed. We conduct simulation studies to examine the operating characteristics and illustrate the proposed method with an example.
Persistent Identifierhttp://hdl.handle.net/10722/146565
ISSN
2015 Impact Factor: 1.36
2015 SCImago Journal Rankings: 1.906
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYin, Gen_HK
dc.contributor.authorShen, Yen_HK
dc.date.accessioned2012-05-02T08:37:02Z-
dc.date.available2012-05-02T08:37:02Z-
dc.date.issued2005en_HK
dc.identifier.citationBiometrics, 2005, v. 61 n. 2, p. 362-369+648en_HK
dc.identifier.issn0006-341Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/146565-
dc.description.abstractClinical trial designs involving correlated data often arise in biomedical research. The intracluster correlation needs to be taken into account to ensure the validity of sample size and power calculations. In contrast to the fixed-sample designs, we propose a flexible trial design with adaptive monitoring and inference procedures. The total sample size is not predetermined, but adaptively reestimated using observed data via a systematic mechanism. The final inference is based on a weighted average of the block-wise test statistics using generalized estimating equations, where the weight for each block depends on cumulated data from the ongoing trial. When there are no significant treatment effects, the devised stopping rule allows for early termination of the trial and acceptance of the null hypothesis. The proposed design updates information regarding both the effect size and within-cluster correlation based on the cumulated data in order to achieve a desired power. Estimation of the parameter of interest and its confidence interval are proposed. We conduct simulation studies to examine the operating characteristics and illustrate the proposed method with an example.en_HK
dc.languageengen_US
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOMen_HK
dc.relation.ispartofBiometricsen_HK
dc.subjectCorrelated dataen_HK
dc.subjectGeneralized estimating equationen_HK
dc.subjectHypothesis testingen_HK
dc.subjectPoweren_HK
dc.subjectSample sizeen_HK
dc.subjectSelf-designing trialen_HK
dc.subject.meshBiometryen_US
dc.subject.meshCluster Analysisen_US
dc.subject.meshComputer Simulationen_US
dc.subject.meshConfidence Intervalsen_US
dc.subject.meshData Interpretation, Statisticalen_US
dc.subject.meshHumansen_US
dc.subject.meshLogistic Modelsen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshNormal Distributionen_US
dc.subject.meshRandomized Controlled Trials As Topic - Methodsen_US
dc.subject.meshResearch Designen_US
dc.subject.meshSample Sizeen_US
dc.subject.meshSensitivity And Specificityen_US
dc.subject.meshTreatment Outcomeen_US
dc.titleAdaptive design and estimation in randomized clinical trials with correlated observationsen_HK
dc.typeArticleen_HK
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1111/j.1541-0420.2005.00333.xen_HK
dc.identifier.pmid16011682-
dc.identifier.scopuseid_2-s2.0-20744447735en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-20744447735&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume61en_HK
dc.identifier.issue2en_HK
dc.identifier.spage362en_HK
dc.identifier.epage369+648en_HK
dc.identifier.isiWOS:000229893900005-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK
dc.identifier.scopusauthoridShen, Y=7404766770en_HK
dc.identifier.citeulike231770-

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