Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/jspui/handle/123456789/17216
Title: Bounded-width confidence interval following optimal sequential analysis of adverse events with binary data.
Authors: Silva, Ivair Ramos
Zhuang, Yan
Keywords: Estimate precision
Coverage probability
Expected time to signal
Clinical trials
Post-market safety surveillance
Issue Date: 2022
Citation: SILVA, I. R.; ZHUANG, Y. Bounded-width confidence interval following optimal sequential analysis of adverse events with binary data. Statistical Methods in Medical Research, v. 31, n. 12, p. 2323–2337, 2022. Disponível em: <https://journals.sagepub.com/doi/10.1177/09622802221122383>. Acesso em: 06 jul. 2023.
Abstract: In sequential testing with binary data, sample size and time to detect a signal are the key performance measures to opti- mize. While the former should be optimized in Phase III clinical trials, minimizing the latter is of major importance in post- market drug and vaccine safety surveillance of adverse events. The precision of the relative risk estimator on termination of the analysis is a meaningful design criterion as well. This paper presents a linear programming framework to find the optimal alpha spending that minimizes expected time to signal, or expected sample size as needed. The solution enables (a) to bound the width of the confidence interval following the end of the analysis, (b) designs with outer signaling thresh- olds and inner non-signaling thresholds, and (c) sequential designs with variable Bernoulli probabilities. To illustrate, we use real data on the monitoring of adverse events following the H1N1 vaccination. The numerical results are obtained using the R Sequential package.
URI: http://www.repositorio.ufop.br/jspui/handle/123456789/17216
metadata.dc.identifier.uri2: https://journals.sagepub.com/doi/10.1177/09622802221122383
metadata.dc.identifier.doi: https://doi.org/10.1177/09622802221122383
ISSN: 1477-0334
Appears in Collections:DEEST - Artigos publicados em periódicos

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