dc.creatorWu, Darong
dc.creatorAkl, Elie A.
dc.creatorGuyatt, Gordon H.
dc.creatorDevereaux, Philip J.
dc.creatorBrignardello Petersen, Romina
dc.creatorPrediger, Barbara
dc.creatorPatel, Krupesh
dc.creatorPatel, Namrata
dc.creatorLu, Taoying
dc.creatorZhang, Yuan
dc.creatorFalavigna, Maicon
dc.creatorSantesso, Nancy
dc.creatorMustafa, Reem A.
dc.creatorZhou, Qi
dc.creatorBriel, Matthias
dc.creatorSchünemann, Holger J.
dc.date.accessioned2014-12-11T17:29:26Z
dc.date.accessioned2019-04-25T23:41:10Z
dc.date.available2014-12-11T17:29:26Z
dc.date.available2019-04-25T23:41:10Z
dc.date.created2014-12-11T17:29:26Z
dc.date.issued2014
dc.identifierTrials 2014, 15:33
dc.identifierdoi:10.1186/1745-6215-15-33
dc.identifierhttp://repositorio.uchile.cl/handle/2250/123557
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/2427898
dc.description.abstractBackground: Although even randomization (that is, approximately 1:1 randomization ratio in study arms) provides the greatest statistical power, designed uneven randomization (DUR), (for example, 1:2 or 1:3) is used to increase participation rates. Until now, no convincing data exists addressing the impact of DUR on participation rates in trials. The objective of this study is to evaluate the epidemiology and to explore factors associated with DUR. Methods: We will search for reports of RCTs published within two years in 25 general medical journals with the highest impact factor according to the Journal Citation Report (JCR)-2010. Teams of two reviewers will determine eligibility and extract relevant information from eligible RCTs in duplicate and using standardized forms. We will report the prevalence of DUR trials, the reported reasons for using DUR, and perform a linear regression analysis to estimate the association between the randomization ratio and the associated factors, including participation rate, type of informed consent, clinical area, and so on. Discussion: A clearer understanding of RCTs with DUR and its association with factors in trials, for example, participation rate, can optimize trial design and may have important implications for both researchers and users of the medical literature.
dc.languageen
dc.publisherBioMed Central Ltd.
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.subjectParticipation rate
dc.titleMethodological survey of designed uneven randomization trials (DU-RANDOM): a protocol
dc.typeArtículos de revistas


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