Composite sequential Monte Carlo test for post-market vaccine safety surveillance.
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFOP |
Texto Completo: | http://www.repositorio.ufop.br/handle/123456789/7179 http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdf https://doi.org/10.1002/sim.6805 |
Resumo: | Group sequential hypothesis testing is now widely used to analyze prospective data. If Monte Carlo simulation is used to construct the signaling threshold, the challenge is how to manage the type I error probability for each one of the multiple tests without losing control on the overall significance level. This paper introduces a valid method for a true management of the alpha spending at each one of a sequence of Monte Carlo tests. The method also enables the use of a sequential simulation strategy for each Monte Carlo test, which is useful for saving computational execution time. Thus, the proposed procedure allows for sequential Monte Carlo test in sequential analysis, and this is the reason that it is called ‘composite sequential’ test. An upper bound for the potential power losses from the proposed method is deduced. The composite sequential design is illustrated through an application for post-market vaccine safety surveillance data. |
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Composite sequential Monte Carlo test for post-market vaccine safety surveillance.Alpha spendingValid p-valuePower lossGroup sequential hypothesis testing is now widely used to analyze prospective data. If Monte Carlo simulation is used to construct the signaling threshold, the challenge is how to manage the type I error probability for each one of the multiple tests without losing control on the overall significance level. This paper introduces a valid method for a true management of the alpha spending at each one of a sequence of Monte Carlo tests. The method also enables the use of a sequential simulation strategy for each Monte Carlo test, which is useful for saving computational execution time. Thus, the proposed procedure allows for sequential Monte Carlo test in sequential analysis, and this is the reason that it is called ‘composite sequential’ test. An upper bound for the potential power losses from the proposed method is deduced. The composite sequential design is illustrated through an application for post-market vaccine safety surveillance data.2017-02-01T13:19:38Z2017-02-01T13:19:38Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSILVA, I. R. Composite sequential Monte Carlo test for post-market vaccine safety surveillance. Statistics in Medicine, v. 35, n. 9, p. 1441-1453, abr. 2016. Disponível em: <http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdf>. Acesso em: 23 jan. 2017.1097-0258http://www.repositorio.ufop.br/handle/123456789/7179http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdfhttps://doi.org/10.1002/sim.6805Silva, Ivair Ramosinfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOP2024-11-10T14:03:00Zoai:repositorio.ufop.br:123456789/7179Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332024-11-10T14:03Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false |
dc.title.none.fl_str_mv |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
title |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
spellingShingle |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. Silva, Ivair Ramos Alpha spending Valid p-value Power loss |
title_short |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
title_full |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
title_fullStr |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
title_full_unstemmed |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
title_sort |
Composite sequential Monte Carlo test for post-market vaccine safety surveillance. |
author |
Silva, Ivair Ramos |
author_facet |
Silva, Ivair Ramos |
author_role |
author |
dc.contributor.author.fl_str_mv |
Silva, Ivair Ramos |
dc.subject.por.fl_str_mv |
Alpha spending Valid p-value Power loss |
topic |
Alpha spending Valid p-value Power loss |
description |
Group sequential hypothesis testing is now widely used to analyze prospective data. If Monte Carlo simulation is used to construct the signaling threshold, the challenge is how to manage the type I error probability for each one of the multiple tests without losing control on the overall significance level. This paper introduces a valid method for a true management of the alpha spending at each one of a sequence of Monte Carlo tests. The method also enables the use of a sequential simulation strategy for each Monte Carlo test, which is useful for saving computational execution time. Thus, the proposed procedure allows for sequential Monte Carlo test in sequential analysis, and this is the reason that it is called ‘composite sequential’ test. An upper bound for the potential power losses from the proposed method is deduced. The composite sequential design is illustrated through an application for post-market vaccine safety surveillance data. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2017-02-01T13:19:38Z 2017-02-01T13:19:38Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
SILVA, I. R. Composite sequential Monte Carlo test for post-market vaccine safety surveillance. Statistics in Medicine, v. 35, n. 9, p. 1441-1453, abr. 2016. Disponível em: <http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdf>. Acesso em: 23 jan. 2017. 1097-0258 http://www.repositorio.ufop.br/handle/123456789/7179 http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdf https://doi.org/10.1002/sim.6805 |
identifier_str_mv |
SILVA, I. R. Composite sequential Monte Carlo test for post-market vaccine safety surveillance. Statistics in Medicine, v. 35, n. 9, p. 1441-1453, abr. 2016. Disponível em: <http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdf>. Acesso em: 23 jan. 2017. 1097-0258 |
url |
http://www.repositorio.ufop.br/handle/123456789/7179 http://onlinelibrary.wiley.com/doi/10.1002/sim.6805/epdf https://doi.org/10.1002/sim.6805 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFOP instname:Universidade Federal de Ouro Preto (UFOP) instacron:UFOP |
instname_str |
Universidade Federal de Ouro Preto (UFOP) |
instacron_str |
UFOP |
institution |
UFOP |
reponame_str |
Repositório Institucional da UFOP |
collection |
Repositório Institucional da UFOP |
repository.name.fl_str_mv |
Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP) |
repository.mail.fl_str_mv |
repositorio@ufop.edu.br |
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1823329294235992064 |