#40 Bayesian Stats for the Speech & Language Sciences, with Allison Hilger and Timo Roettger
Learning Bayesian Statistics
How to Write a Model With Multiple Dependent Variables
In his field, we have a very limited sta background. And even the idea of building a model for your data was kind of new to me. The challenge is that it's ust not very well known in my field. But there are some of us who are really excited about using basian statistics. Yeoh, because light can be seriously used, especially in telegraphy and other fields where you're also disrupting everything just by doing this one thing at the same time.
We all know about these accidental discoveries — penicillin, the heating power of microwaves, or the famous (and delicious) tarte tatin. I don’t know why, but I just love serendipity. And, as you’ll hear, this episode is deliciously full of it…
Thanks to Allison Hilger and Timo Roettger, we’ll discover the world of linguistics, how Bayesian stats are helpful there, and how Paul Bürkner’s BRMS package has been instrumental in this field. To my surprise — and perhaps yours — the speech and language sciences are pretty quantitative and computational!
As she recently discovered Bayesian stats, Allison will also tell us about the challenges she’s faced from advisors and reviewers during her PhD at Northwestern University, and the advice she’d have for people in the same situation.
Allison is now an Assistant Professor at the University of Colorado Boulder. The overall goal in her research is to improve our understanding of motor speech control processes, in order to inform effective speech therapy treatments for improved speech naturalness and intelligibility. Allison also worked clinically as a speech-language pathologist in Chicago for a year. As a new Colorado resident, her new hobbies include hiking, skiing, and biking — and then reading or going to dog parks when she’s to tired.
Holding a PhD in linguistics from the University of Cologne, Germany, Timo is an Associate Professor for linguistics at the University of Oslo, Norway. Timo tries to understand how people communicate their intentions using speech – how are speech signals retrieved; how do people learn and generalize? Timo is also committed to improving methodologies across the language sciences in light of the replication crisis, with a strong emphasis on open science.
Most importantly, Timo loves hiking, watching movies or, even better, watching people play video games!
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, Jonathan Sedar, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt and Andrew Moskowitz.
Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)
Links from the show:
- Allison's website: https://allisonhilger.com/
- Allison on Twitter: https://twitter.com/drahilger
- Allison's motor speech lab: https://www.colorado.edu/lab/motor-speech/
- Timo's website: https://www.simplpoints.com/
- Timo on Twitter: https://twitter.com/TimoRoettger
- Bayesian regression modeling (for factorial designs) -- A tutorial: https://psyarxiv.com/cdxv3
- An Introduction to Bayesian Multilevel Models Using brms -- A Case Study of Gender Effects on Vowel Variability in Standard Indonesian: https://biblio.ugent.be/publication/8624552/file/8624553.pdf
- Longitudinal Growth in Intelligibility of Connected Speech From 2 to 8 Years in Children With Cerebral Palsy -- A Novel Bayesian Approach: https://pubs.asha.org/doi/10.1044/2020_JSLHR-20-00181
- LBS #35 The Past, Present & Future of BRMS, with Paul Bürkner: https://www.learnbayesstats.com/episode/35-past-present-future-brms-paul-burkner
- LBS #16 Bayesian Statistics the Fun Way, with Will Kurt: https://www.learnbayesstats.com/episode/16-bayesian-statistics-the-fun-way-with-will-kurt
- Will Kurt's Bayesian Statistics The Fun Way: https://nostarch.com/learnbayes
- LBS #20 Regression and Other Stories, with Andrew Gelman, Jennifer Hill & Aki Vehtari: https://www.learnbayesstats.com/episode/20-regression-and-other-stories-with-andrew-gelman-jennifer-hill-aki-vehtari
- Regression and Other Stories examples: https://avehtari.github.io/ROS-Examples/
Remember Everything You Learn from Podcasts
