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- Publisher Website: 10.1111/j.1541-0420.2005.00333.x
- Scopus: eid_2-s2.0-20744447735
- PMID: 16011682
- WOS: WOS:000229893900005
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Article: Adaptive design and estimation in randomized clinical trials with correlated observations
Title | Adaptive design and estimation in randomized clinical trials with correlated observations |
---|---|
Authors | |
Keywords | Correlated data Generalized estimating equation Hypothesis testing Power Sample size Self-designing trial |
Issue Date | 2005 |
Publisher | Blackwell 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? |
Abstract | Clinical 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 Identifier | http://hdl.handle.net/10722/146565 |
ISSN | 2023 Impact Factor: 1.4 2023 SCImago Journal Rankings: 1.480 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yin, G | en_HK |
dc.contributor.author | Shen, Y | en_HK |
dc.date.accessioned | 2012-05-02T08:37:02Z | - |
dc.date.available | 2012-05-02T08:37:02Z | - |
dc.date.issued | 2005 | en_HK |
dc.identifier.citation | Biometrics, 2005, v. 61 n. 2, p. 362-369+648 | en_HK |
dc.identifier.issn | 0006-341X | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/146565 | - |
dc.description.abstract | Clinical 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.language | eng | en_US |
dc.publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM | en_HK |
dc.relation.ispartof | Biometrics | en_HK |
dc.subject | Correlated data | en_HK |
dc.subject | Generalized estimating equation | en_HK |
dc.subject | Hypothesis testing | en_HK |
dc.subject | Power | en_HK |
dc.subject | Sample size | en_HK |
dc.subject | Self-designing trial | en_HK |
dc.subject.mesh | Biometry | en_US |
dc.subject.mesh | Cluster Analysis | en_US |
dc.subject.mesh | Computer Simulation | en_US |
dc.subject.mesh | Confidence Intervals | en_US |
dc.subject.mesh | Data Interpretation, Statistical | en_US |
dc.subject.mesh | Humans | en_US |
dc.subject.mesh | Logistic Models | en_US |
dc.subject.mesh | Models, Statistical | en_US |
dc.subject.mesh | Normal Distribution | en_US |
dc.subject.mesh | Randomized Controlled Trials As Topic - Methods | en_US |
dc.subject.mesh | Research Design | en_US |
dc.subject.mesh | Sample Size | en_US |
dc.subject.mesh | Sensitivity And Specificity | en_US |
dc.subject.mesh | Treatment Outcome | en_US |
dc.title | Adaptive design and estimation in randomized clinical trials with correlated observations | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Yin, G: gyin@hku.hk | en_HK |
dc.identifier.authority | Yin, G=rp00831 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1111/j.1541-0420.2005.00333.x | en_HK |
dc.identifier.pmid | 16011682 | - |
dc.identifier.scopus | eid_2-s2.0-20744447735 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-20744447735&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 61 | en_HK |
dc.identifier.issue | 2 | en_HK |
dc.identifier.spage | 362 | en_HK |
dc.identifier.epage | 369+648 | en_HK |
dc.identifier.isi | WOS:000229893900005 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.identifier.scopusauthorid | Yin, G=8725807500 | en_HK |
dc.identifier.scopusauthorid | Shen, Y=7404766770 | en_HK |
dc.identifier.citeulike | 231770 | - |
dc.identifier.issnl | 0006-341X | - |