Journal of biopharmaceutical statistics
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This review article sets out to examine the Type I error rates used in noninferiority trials. Most papers regarding noninferiority trials only state Type I error rate without mentioning clearly which Type I error rate is evaluated. Therefore, the Type I error rate in one paper is often different from the Type I error rate in another paper, which can confuse readers and makes it difficult to understand papers. ⋯ The conditional across-trial Type I error rate is also briefly discussed. In noninferiority trials comparing a new treatment with an active control without a placebo arm, it is argued that the within-trial Type I error rate should be controlled in order to obtain approval of the new treatment from the regulatory agencies. I hope that this article can help readers understand the difference between two paradigms employed in noninferiority trials.
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The world of medical devices while highly diverse is extremely innovative, and this facilitates the adoption of innovative statistical techniques. Statisticians in the Center for Devices and Radiological Health (CDRH) at the Food and Drug Administration (FDA) have provided leadership in implementing statistical innovations. The innovations discussed include: the incorporation of Bayesian methods in clinical trials, adaptive designs, the use and development of propensity score methodology in the design and analysis of non-randomized observational studies, the use of tipping-point analysis for missing data, techniques for diagnostic test evaluation, bridging studies for companion diagnostic tests, quantitative benefit-risk decisions, and patient preference studies.