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http://www.repositorio.ufop.br/jspui/handle/123456789/9402
Título: | Type I error probability spending for post-market drug and vaccine safety surveillancewith poisson data. |
Autor(es): | Silva, Ivair Ramos |
Palavras-chave: | Sequential probability ratio test Expected number of events to signal Log-exp alpha spending |
Data do documento: | 2017 |
Referência: | SILVA, I. R. Type I error probability spending for post-market drug and vaccine safety surveillancewith poisson data. Methodology and Computing in Applied Probability, v.01, p.1-12, 2017. Disponível em: <https://link.springer.com/article/10.1007/s11009-017-9586-z>. Acesso em: 16 jan. 2018. |
Resumo: | Statistical sequential hypothesis testing is meant to analyze cumulative data accruing in time. The methods can be divided in two types, group and continuous sequential approaches, and a question that arises is if one approach suppresses the other in some sense. For Poisson stochastic processes, we prove that continuous sequential analysis is uniformly better than group sequential under a comprehensive class of statistical performance measures. Hence, optimal solutions are in the class of continuous designs. This paper also offers a pioneer study that compares classical Type I error spending functions in terms of expected number of events to signal. This was done for a number of tuning parameters scenarios. The results indicate that a log-exp shape for the Type I error spending function is the best choice in most of the evaluated scenarios. |
URI: | http://www.repositorio.ufop.br/handle/123456789/9402 |
Link para o artigo: | https://link.springer.com/article/10.1007/s11009-017-9586-z |
DOI: | https://doi.org/10.1007/s11009-017-9586-z |
ISSN: | 1573-7713 |
Aparece nas coleções: | DEEST - Artigos publicados em periódicos |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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ARTIGO_TypeIPoisson.pdf Restricted Access | 542,82 kB | Adobe PDF | Visualizar/Abrir |
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