Casual Inference Lucy D'Agostino McGowan and Ellie Murray

Alyssa Bilinski, Peterson Family Assistant Professor of Health Policy, and Assistant Professor of Biostatistics, at Brown University School of Public Health. Her research focuses on developing novel methods for policy evaluation and applying these to identify interventions that most efficiently improve population health and well-being.
Episode notes:
PNAS paper: https://www.pnas.org/doi/full/10.1073/pnas.2302528120
Shuo Feng’s pre-print: https://www.medrxiv.org/content/10.1101/2024.04.08.24305335v1
Our uncertainty paper: https://pubmed.ncbi.nlm.nih.gov/33475686/
Follow along on Twitter:
Alyssa: @ambilinski The American Journal of Epidemiology: @AmJEpi
Ellie: @EpiEllie
Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade
Edited by Cameron Bopp

Edward Kennedy Associate Professor, Department of Statistics & Data Science, Carnegie Mellon.
ehkennedy.com
Evaluating a Targeted Minimum Loss-Based Estimator for Capture-Recapture Analysis: An Application to HIV Surveillance in San Francisco, California: https://academic.oup.com/aje/article/193/4/673/7425624
Doubly Robust Capture-Recapture Methods for Estimating Population Size: https://www.tandfonline.com/doi/full/10.1080/01621459.2023.2187814
Follow along on Twitter:
The American Journal of Epidemiology: @AmJEpi
Ellie: @EpiEllie
Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade
Edited by Cameron Bopp

Sheree Bekker & Stephen Mumford are Co-directors of the Feminist Sport Lab and have a book coming soon: “Open Play: the case for feminist sport”, coming Spring 2025. Reaktion Books (UK), University of Chicago Press (US).
Sheree Bekker: Associate Professor, University of Bath, Department for Health,
Centre for Qualitative Research
Centre for Health and Injury and Illness Prevention in Sport
Stephen Mumford, Professor of Metaphysics, Durham University  A
Author of Dispositions (Oxford, 1998), Russell on Metaphysics (Routledge, 2003), Laws in Nature (Routledge, 2004), David Armstrong (Acumen, 2007), Watching Sport: Aesthetics, Ethics and Emotion (Routledge, 2011), Getting Causes from Powers (Oxford, 2011 with Rani Lill Anjum), Metaphysics: a Very Short Introduction (Oxford, 2012) and Causation: a Very Short Introduction (Oxford, 2013 with Rani Lill Anjum). I was editor of George Molnar's posthumous Powers: a Study in Metaphysics (Oxford, 2003) and Metaphysics and Science (Oxford, 2013 with Matthew Tugby). Feminist Sport Lab: https://www.feministsportlab.com
Causation: A Very Short Introduction by Stephen Mumford & Rani Lill Anjum: https://academic.oup.com/book/616
Faye Norby, Iditarod champion & epidemiologist: https://www.kfyrtv.com/2024/03/28/faye-norby-finishes-iditarod-trail-womens-foot-champion/?outputType=amp 
Follow along on Twitter:
The American Journal of Epidemiology: @AmJEpi
Ellie: @EpiEllie
Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade
Edited by Cameron Bopp

Erick Scott is founder of cStructure, a causal science startup. Erick has expertise in medicine, public health, and computational biology.
info@cStructure.io
“A causal roadmap for generating high-quality real-world evidence” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603361/
Follow along on Twitter:
The American Journal of Epidemiology: @AmJEpi
Ellie: @EpiEllie
Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade
Edited by Cameron Bopp

Nima Hejazi is an assistant professor in biostatistics at Harvard University. His methodological work often draws upon tools and ideas from semi- and non-parametric inference, high-dimensional and large-scale inference, targeted or debiased machine learning (e.g., targeted minimum loss estimation, method of sieves), and computational statistics.
Surprised by the Hot Hand Fallacy? A Truth in the Law of Small Numbers by Joshua B. Miller & Adam Sanjurjo: https://www.jstor.org/stable/44955325
Nima is on Twitter/X as @nshejazi (https://twitter.com/nshejazi) and my academic webpage is https://nimahejazi.org
Recent translational review paper (intended for the infectious disease science community) I was involved in describing some causal/statistical frameworks for evaluating immune markers as mediators / surrogate endpoints: https://pubmed.ncbi.nlm.nih.gov/38458870/
The tlverse software ecosystem is on GitHub at https://github.com/tlverse and the tlverse handbook is freely available at https://tlverse.org/tlverse-handbook/
Dr. Hejazi annually co-teaches a causal mediation analysis workshop at SER, and notes from the latest offering are freely available at https://codex.nimahejazi.org/ser2023_mediation_workshop/
Follow along on Twitter:
The American Journal of Epidemiology: @AmJEpi
Ellie: @EpiEllie
Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade
Edited by Cameron Bopp

Aaditya Ramdas is an assistant professor at Carnegie Mellon University, in the Departments of Statistics and Machine Learning. His research interests include game-theoretic statistics and sequential anytime-valid inference, multiple testing and post-selection inference, and uncertainty quantification for machine learning (conformal prediction, calibration). His applied areas of interest include neuroscience, genetics and auditing (real-estate, finance, elections). Aaditya received the IMS Peter Gavin Hall Early Career Prize, the COPSS Emerging Leader Award, the Bernoulli New Researcher Award, the NSF CAREER Award, the Sloan fellowship in Mathematics, and faculty research awards from Adobe and Google. He also spends 20% of his time at Amazon working on causality and sequential experimentation.
Aaditya’s website: https://www.stat.cmu.edu/~aramdas/
Game theoretic statistics resources
Aaditya’s course, Game-theoretic probability, statistics, and learning:
https://www.stat.cmu.edu/~aramdas/gtpsl/index.html
Papers of interest:
Time-uniform central limit theory and asymptotic confidence sequences: https://arxiv.org/abs/2103.06476
Game-theoretic statistics and safe anytime-valid inference: https://arxiv.org/abs/2210.01948
Discussion papers:
Safe Testing: https://arxiv.org/abs/1906.07801
Testing by Betting: https://academic.oup.com/jrsssa/article/184/2/407/7056412
Estimating means of bounded random variables by betting: https://academic.oup.com/jrsssb/article/86/1/1/7043257 
Follow along on Twitter:
The American Journal of Epidemiology: @AmJEpi
Ellie: @EpiEllie
Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade
Edited by Cameron Bopp