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 hbiostat.org
Sequential Bayesian Designs for Rapid Learning in COVID-19 Clinical Trials - Statistical Thinking
| | fharrell.com
Goal-Driven Flexible Bayesian Design - Statistical Thinking
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| | The majority of clinicals trials that are successfully launched end with equivocal results, with confidence intervals that are too wide to allow drawing a conclusion other than "the money was spent". This is due to constraints of fixed budgeting models, gaming MCIDs in sample size calculations, using low-information outcome variables, pretending that the computed sample size is estimated without error, avoiding sequential designs, and other reasons. There are also major opportunities lost for stopping studies earlier for futility. These problems may be avoided by instilling discipline in the choice of MCID and the choice of outcome, and using flexible Bayesian fully sequential designs without limiting the number of data looks. To understand why this works it...
| | www.fharrell.com
Fundamental Principles of Statistics - Statistical Thinking
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| | This brief note catalogs what I feel are some of the most important principles to guide statistical practice.
| | rpsychologist.com
Bayesian Inference - an Interactive Visualization
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| | isaacslavitt.com
Isaac Slavitt: Solving the Bayesian German Tank problem with PyMC and PyStan
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| [AI summary] A Python developer solves the German Tank Problem using Markov Chain Monte Carlo methods, comparing implementations in Sampyl, PyMC3, and PyStan.