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

Ivair R. Silva, Judith C. Maro, Martin Kulldorff

2021Statistics in Medicine11 citationsDOIOpen Access PDF

Abstract

In 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.

Topics & Concepts

Computer sciencePoisson distributionBinary dataCoronavirus disease 2019 (COVID-19)Statistical hypothesis testingBinary numberSequential analysisBernoulli trialClinical trialSample size determinationStatisticsData miningMedicineMathematicsDiseaseInfectious disease (medical specialty)ArithmeticPathologyStatistical Methods in Clinical TrialsPharmacovigilance and Adverse Drug ReactionsHealth Systems, Economic Evaluations, Quality of Life
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