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Sequential Analysis
Design Methods and Applications
Volume 38, 2019 - Issue 1
129
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Articles

Exact conditional maximized sequential probability ratio test adjusted for covariates

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Pages 115-133 | Received 19 Jul 2018, Accepted 24 Jan 2019, Published online: 13 May 2019
 

Abstract

Sequential analysis is now commonly used for post-market drug and vaccine safety surveillance, and a Poisson stochastic process is typically used for rare adverse events. The conditional maximized sequential probability ratio test, CMaxSPRT, is a powerful tool when there is uncertainty in the estimated expected counts under the null hypothesis. This paper derives exact critical values for CMaxSPRT, as well as statistical power and expected time to signal. This is done for both continuous and group sequential analysis, and for different rejection boundaries. It is also shown how to adjust for covariates in the sequential design. A table of critical values is provided for selected parameters and rejection boundaries, while new functions in the R Sequential package can be used for other calculations. In addition, the method is illustrated for monitoring adverse events after pediarix vaccination data.

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Acknowledgments

We are also grateful for the very important improvements suggested by the Associate Editor and referees.

Additional information

Funding

This research was funded by the National Institute of General Medical Sciences, USA, grant #RO1GM108999. The first author has received additional support from Fundação de Amparo à Pesquisa do Estado de Minas Gerais, Minas Gerais, Brasil (FAPEMIG).

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