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dc.contributor.authorSilva, Ivair Ramos-
dc.contributor.authorLopes, Wilson Araujo-
dc.contributor.authorDias, Philipe-
dc.contributor.authorYih, W. Katherine-
dc.identifier.citationSILVA, I. R. et al. Alpha spending for historical versus surveillance Poisson data with CMaxSPRT. Statistics in Medicine, v. 38, p. 2126– 2138, 2019. Disponível em: <>. Acesso em: 19 mar. 2019.pt_BR
dc.description.abstractSequential analysis hypothesis testing is now an important tool for postmarket drug and vaccine safety surveillance. When the number of adverse events accruing in time is assumed to follow a Poisson distribution, and if the baseline Poisson rate is assessed only with uncertainty, the conditional maximized sequential probability ratio test, CMaxSPRT, is a formal solution. CMaxSPRT is based on comparing monitored data with historical matched data, and it was primarily developed under a flat signaling threshold. This paper demonstrates that CMaxSPRT can be performed under nonflat thresholds too.We pose the discussion in the light of the alpha spending approach. In addition, we offer a rule of thumb for establishing the best shape of the signaling threshold in the sense of minimizing expected time to signal and expected sample size. An example involving surveillance for adverse events after influenza vaccination is used to illustrate the method.pt_BR
dc.subjectClinical trialspt_BR
dc.subjectPostmarket vaccine safety surveillancept_BR
dc.subjectSample sizept_BR
dc.subjectTime to signalpt_BR
dc.titleAlpha spending for historical versus surveillance Poisson data with CMaxSPRT.pt_BR
dc.typeArtigo publicado em periodicopt_BR
Appears in Collections:DEEST - Artigos publicados em periódicos

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