Frank Harrell's guest appearances

Frank Harrell

Plenary Session

Learning Bayesian Statistics

Casual Inference

Sean Taylor

Mark Lewis

John McConnell

David Spiegelhalter

Carl Hart

Marty Makary

Emily Oster

Andrew Gelman

Adam Cifu

Vinay Prasad

Jenny Gill

Michael Lee

Baba Brinkman

Tom DeLoughery

Dan Morgan

OwlTail

As a podcaster, I discovered that there are guests for which the hardest is to know when to stop the conversation. They could talk for hours and that would make for at least 10 fantastic episodes. Frank Harrell is one of those guests. To me, our conversation was both fascinating — thanks to Frank’s expertise and the width and depth of topics we touched on — and frustrating — I still had a gazillion questions for him!But rest assured, we talked about intent to treat and randomization, proportional odds, clinical trial design, bio stats and covid19, and even which mistakes you should do to learn Bayes stats — yes, you heard right, which mistakes. Anyway, I can’t tell you everything here — you’ll just have to listen to the episode!A long time Bayesian, Frank is a Professor of Biostatistics in the School of Medicine at Vanderbilt University. His numerous research interests include predictive models and model validation, Bayesian clinical trial design and Bayesian models, drug development, and clinical research.He holds a PhD in biostatistics from the University of North Carolina, and did his Bachelor in mathematics at the University of Alabama in Birmingham.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin and Philippe Labonde.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Frank's website and courses: https://hbiostat.org/Frank's blog: https://www.fharrell.com/Frank on Twitter: https://twitter.com/f2harrellCOVID-19 Randomized Clinical Trial Design: https://hbiostat.org/proj/covid19/Frank on GitHub: https://github.com/harrelfeRegression Modeling Strategies repository: https://github.com/harrelfe/rmsBiostatistics for Biomedical Research repository: https://github.com/harrelfe/bbrBayesian Approaches to Randomized Trials, Spiegelhalter et al.: http://hbiostat.org/papers/Bayes/spi94bay.pdfStatistical Rethinking, Richard McElreath: http://xcelab.net/rm/statistical-rethinking/LBS #20, Regression and Other Stories, with Andrew Gelman, Jennifer Hill &amp; Aki Vehtari: https://www.learnbayesstats.com/episode/20-regression-and-other-stories-with-andrew-gelman-jennifer-hill-aki-vehtariDavid Spiegelhalter, The Art of Statistics -- Learning from Data: https://www.amazon.fr/Art-Statistics-Learning-Data/dp/0241398630Confidence intervals vs. Bayesian intervals, E.T. Jaynes: https://bayes.wustl.edu/etj/articles/confidence.pdfThis podcast uses the following third-party services for analysis: Podcorn - https://podcorn.com/privacy

As a podcaster, I discovered that there are guests for which the hardest is to know when to stop the conversation. They could talk for hours and that would make for at least 10 fantastic episodes. Frank Harrell is one of those guests. To me, our conversation was both fascinating — thanks to Frank’s expertise and the width and depth of topics we touched on — and frustrating — I still had a gazillion questions for him!But rest assured, we talked about intent to treat and randomization, proportional odds, clinical trial design, bio stats and covid19, and even which mistakes you should do to learn Bayes stats — yes, you heard right, which mistakes. Anyway, I can’t tell you everything here — you’ll just have to listen to the episode!A long time Bayesian, Frank is a Professor of Biostatistics in the School of Medicine at Vanderbilt University. His numerous research interests include predictive models and model validation, Bayesian clinical trial design and Bayesian models, drug development, and clinical research.He holds a PhD in biostatistics from the University of North Carolina, and did his Bachelor in mathematics at the University of Alabama in Birmingham.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at <a href="https://bababrinkman.com/" rel="noopener noreferrer nofollow" target="_blank">https://bababrinkman.com/</a> !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin and Philippe Labonde.Visit <a href="https://www.patreon.com/learnbayesstats" rel="noopener noreferrer nofollow" target="_blank">https://www.patreon.com/learnbayesstats</a> to unlock exclusive Bayesian swag ;)Links from the show:<ul><li>Frank's website and courses: <a href="https://hbiostat.org/" rel="noopener noreferrer nofollow" target="_blank">https://hbiostat.org/</a></li><li>Frank's blog: <a href="https://www.fharrell.com/" rel="noopener noreferrer nofollow" target="_blank">https://www.fharrell.com/</a></li><li>Frank on Twitter: <a href="https://twitter.com/f2harrell" rel="noopener noreferrer nofollow" target="_blank">https://twitter.com/f2harrell</a></li><li>COVID-19 Randomized Clinical Trial Design: <a href="https://hbiostat.org/proj/covid19/" rel="noopener noreferrer nofollow" target="_blank">https://hbiostat.org/proj/covid19/</a></li><li>Frank on GitHub: <a href="https://github.com/harrelfe" rel="noopener noreferrer nofollow" target="_blank">https://github.com/harrelfe</a></li><li>Regression Modeling Strategies repository: <a href="https://github.com/harrelfe/rms" rel="noopener noreferrer nofollow" target="_blank">https://github.com/harrelfe/rms</a></li><li>Biostatistics for Biomedical Research repository: <a href="https://github.com/harrelfe/bbr" rel="noopener noreferrer nofollow" target="_blank">https://github.com/harrelfe/bbr</a></li><li>Bayesian Approaches to Randomized Trials, Spiegelhalter et al.: <a href="http://hbiostat.org/papers/Bayes/spi94bay.pdf" rel="noopener noreferrer nofollow" target="_blank">http://hbiostat.org/papers/Bayes/spi94bay.pdf</a></li><li>Statistical Rethinking, Richard McElreath: <a href="http://xcelab.net/rm/statistical-rethinking/" rel="noopener noreferrer nofollow" target="_blank">http://xcelab.net/rm/statistical-rethinking/</a></li><li>LBS #20, Regression and Other Stories, with Andrew Gelman, Jennifer Hill &amp; Aki Vehtari: <a href="https://www.learnbayesstats.com/episode/20-regression-and-other-stories-with-andrew-gelman-jennifer-hill-aki-vehtari" rel="noopener noreferrer nofollow" target="_blank">https://www.learnbayesstats.com/episode/20-regression-and-other-stories-with-andrew-gelman-jennifer-hill-aki-vehtari</a></li><li>David Spiegelhalter, The Art of Statistics -- Learning from Data: <a href="https://www.amazon.fr/Art-Statistics-Learning-Data/dp/0241398630" rel="noopener noreferrer nofollow" target="_blank">https://www.amazon.fr/Art-Statistics-Learning-Data/dp/0241398630</a></li><li>Confidence intervals vs. Bayesian intervals, E.T. Jaynes: <a href="https://bayes.wustl.edu/etj/articles/confidence.pdf" rel="noopener noreferrer nofollow" target="_blank">https://bayes.wustl.edu/etj/articles/confidence.pdf</a></li></ul>This podcast uses the following third-party services for analysis: Podcorn - <a href="https://podcorn.com/privacy" rel="nofollow" target="_blank">https://podcorn.com/privacy</a>

#45 Biostats & Clinical Trial Design, with Frank Harrell

Ellie Murray and Lucy D'Agostino McGowan discuss Bayesian statistics, model validation, and more, with special guest Dr. Frank Harrell from the Department of Biostatistics at Vanderbilt University. 🤷‍♀️What does it mean to be Bayesian? 🤷‍♀️How can we decide if our models are good? 📈Frank's COVID trial resource hub  📈Betsy Ogburn's COVID trial protocol hub 👨‍🏫Frank's Free Biostatistics in Biomedical Research Course 🐍Lucy's tweetorial on Type 1 error and including nonlinear terms in models Follow along on Twitter:  The American Journal of Epidemiology: @AmJEpi Ellie: @EpiEllie Lucy: @LucyStats Frank: @f2harrell  🎶 Our intro/outro music is courtesy of Joseph McDade. 👩‍🎨 Our artwork is by Allison Horst.

Ellie Murray and Lucy D'Agostino McGowan discuss Bayesian statistics, model validation, and more, with special guest Dr. Frank Harrell from the Department of Biostatistics at Vanderbilt University. 🤷‍♀️What does it mean to be Bayesian? 🤷‍♀️How can we decide if our models are good? 📈Frank's <a href="http://hbiostat.org/proj/covid19/" rel="nofollow" target="_blank">COVID trial resource hub</a> 📈Betsy Ogburn's <a href="https://covidcp.org" rel="nofollow" target="_blank">COVID trial protocol hub</a> 👨‍🏫Frank's <a href="https://hbiostat.org/bbr/" rel="nofollow" target="_blank">Free Biostatistics in Biomedical Research Course</a> 🐍Lucy's <a href="https://twitter.com/AmJEpi/status/1181675138942554113?s=20" rel="nofollow" target="_blank">tweetorial on Type 1 error and including nonlinear terms in models</a> Follow along on Twitter: <ul> <li>The American Journal of Epidemiology: <a href="https://twitter.com/amjepi" rel="nofollow" target="_blank">@AmJEpi</a></li> <li>Ellie: <a href="https://twitter.com/epiellie" rel="nofollow" target="_blank">@EpiEllie</a></li> <li>Lucy: <a href="https://twitter.com/lucystats" rel="nofollow" target="_blank">@LucyStats</a></li> <li>Frank: <a href="https://twitter.com/f2harrell" rel="nofollow" target="_blank">@f2harrell</a></li> </ul> 🎶 Our intro/outro music is courtesy of <a href="https://josephmcdade.com/music" rel="nofollow" target="_blank">Joseph McDade</a>. 👩‍🎨 Our artwork is by <a href="https://twitter.com/allison_horst" rel="nofollow" target="_blank">Allison Horst</a>.

Getting Bayesian with Frank Harrell | Episode 11

We're back with more questions of the week! Our first question, from Ian Straehley, is inspired by the USMLE Step 2 CK; our second question, from Audrey Tran, is on deciding on a medical specialty. We end the episode with an interview with Dr. Frank Harrell of Vanderbilt University on the Bayesian approach to statistical thinking.Back us on Patreon! www.patreon.com/plenarysession

We're back with more questions of the week! Our first question, from Ian Straehley, is inspired by the USMLE Step 2 CK; our second question, from Audrey Tran, is on deciding on a medical specialty. We end the episode with an interview with Dr. Frank Harrell of Vanderbilt University on the Bayesian approach to statistical thinking. Back us on Patreon! <a href="http://www.patreon.com/plenarysession" rel="nofollow" target="_blank">www.patreon.com/plenarysession</a>

2.06 Heart Failure, Choosing a Specialty, & the Bayesian Approach with Dr. Frank Harrell