Exact sequential test for clinical trials and post-market drug and vaccine safety surveillance with Poisson and binary data.

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dc.contributor.authorSilva, Ivair Ramos
dc.contributor.authorMaro, Judith
dc.contributor.authorKulldorff, Martin
dc.date.accessioned2023-01-18T17:43:11Z
dc.date.available2023-01-18T17:43:11Z
dc.date.issued2021pt_BR
dc.description.abstractIn sequential analysis, hypothesis testing is performed repeatedly in a prospective manner as data accrue over time to quickly arrive at an accurate conclusion or decision. In this tutorial paper, detailed explanations are given for both designing and operating sequential testing. We describe the calculation of exact thresholds for stopping or signaling, statistical power, expected time to signal, and expected sample sizes for sequential analysis with Poisson and binary type data. The calculations are run using the package Sequential, constructed in R language. Real data examples are inspired on clinical trials practice, such as the current efforts to develop treatments to face the COVID-19 pandemic, and the comparison of treatments of osteoporosis. In addition, we mimic the monitoring of adverse events following influenza vaccination and Pediarix vaccination.pt_BR
dc.identifier.citationSILVA, I. R.; MARO, J.; KULLDORFF, M. Exact sequential test for clinical trials and post-market drug and vaccine safety surveillance with Poisson and binary data. Statistics in Medicine, v. 40, n. 22, 2021. Disponível em: <https://onlinelibrary.wiley.com/doi/full/10.1002/sim.9094>. Acesso em: 06 jul. 2022.pt_BR
dc.identifier.doihttps://doi.org/10.1002/sim.9094pt_BR
dc.identifier.issn1097-0258
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/15986
dc.identifier.uri2https://onlinelibrary.wiley.com/doi/full/10.1002/sim.9094pt_BR
dc.language.isoen_USpt_BR
dc.rightsrestritopt_BR
dc.subjectAdaptive designpt_BR
dc.subjectAlpha spendingpt_BR
dc.subjectContinuous monitoringpt_BR
dc.subjectGroup sequentialpt_BR
dc.titleExact sequential test for clinical trials and post-market drug and vaccine safety surveillance with Poisson and binary data.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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