Exact sequential test for clinical trials and post-market drug and vaccine safety surveillance with Poisson and binary data.
Ivair R SilvaJudith MaroMartin KulldorffPublished in: Statistics in medicine (2021)
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.
Keyphrases
- clinical trial
- electronic health record
- big data
- density functional theory
- healthcare
- primary care
- public health
- wastewater treatment
- ionic liquid
- data analysis
- molecular dynamics simulations
- autism spectrum disorder
- machine learning
- postmenopausal women
- randomized controlled trial
- high resolution
- mass spectrometry
- phase ii
- bone mineral density
- decision making
- phase iii
- double blind