Ann: COVID ARDS Trial Topline 60-Day Results, page-298

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    Here is a source for people who are actually interested in learning about multiplicity and not just debating what they think they know about it:

    https://academic.oup.com/ije/article/46/2/746/2741997

    An introduction to multiplicity issues in clinical trials: the what, why, when and how


    International Journal of Epidemiology
    , Volume 46, Issue 2, April 2017, Pages 746–755,

    https://doi.org/10.1093/ije/dyw320

    Published:
    26 December 2016

    Abstract

    In clinical trials it is not uncommon to face a multiple testing problem which can have an impact on both type I and type II error rates, leading to inappropriate interpretation of trial results. Multiplicity issues may need to be considered at the design, analysis and interpretation stages of a trial. The proportion of trial reports not adequately correcting for multiple testing remains substantial. The purpose of this article is to provide an introduction to multiple testing issues in clinical trials, and to reduce confusion around the need for multiplicity adjustments. We use a tutorial, question-and-answer approach to address the key issues of why, when and how to consider multiplicity adjustments in trials. We summarize the relevant circumstances under which multiplicity adjustments ought to be considered, as well as options for carrying out multiplicity adjustments in terms of trial design factors including Population, Intervention/Comparison, Outcome, Time frame and Analysis (PICOTA). Results are presented in an easy-to-use table and flow diagrams. Confusion about multiplicity issues can be reduced or avoided by considering the potential impact of multiplicity on type I and II errors and, if necessary pre-specifying statistical approaches to either avoid or adjust for multiplicity in the trial protocol or analysis plan.




 
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