Casual Inference

Apr 10 2025 63 ep. 58 mins 2.2k

Casual Inference Podcast artwork

Keep it casual with the Casual Inference podcast. Your hosts Lucy D'Agostino McGowan and Ellie Murray talk all things epidemiology, statistics, data science, causal inference, and public health. Sponsored by the American Journal of Epidemiology.

Copy RSS

Subscribe on Podcast Addict

Propensity Scores, R Packages, and Practical Advice with Noah Greifer | Season 6 Episode 3

Apr 10 2025 82 mins

Noah Greifer is a statistical consultant and programmer at Harvard University. Episode notes: WeightIt package: https://ngreifer.github.io/WeightIt/ MatchIt package: https://kosukeimai.github.io/MatchIt/ Noah's awesome Stack Exchange post: https://stats.stackexchange.com/a/544958 Follow along on Bluesky: Noah: @noahgreifer.bsky.social Ellie: @EpiEllie.bsky.social Lucy: @

Causal Assumptions and Large Language Models | Season 6 Episode 2

Mar 27 2025 51 mins

Lucy and Ellie chat about large language models, chat interfaces, and causal inference. Do LLMs Act as Repositories of Causal Knowledge?: https://arxiv.org/html/2412.10635v1 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.

Data Integration for Impact with Len Testa | Season 6 Episode 1

Feb 28 2025 44 mins

Lucy chats with Len Testa about a recent analysis he did which combined over 150 publicly available data sources to answer a question about the affordability of Disney World. Len's Deep Dive Post on the Touring Plans Blog [Blog Post] Wall Street Journal Artcile, "Even Disney Is Worried About the High Cost of a Disney Vacation" [Article] Follow along on Bluesky: Len: @lentesta.b

Starting the Conversation on Models with Alyssa Bilinski | Season 5 Episode 11

Jul 10 2024 48 mins

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.

Flexible methods with Edward Kennedy | Season 5 Episode 10

Jun 26 2024 38 mins

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 S

What Sports and Feminism can tell us about Causal Inference with Sheree Bekker & Stephen Mumford | Season 5 Episode 9

Jun 12 2024 49 mins

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

Observational Causal Analyses with Erick Scott | Season 5 Episode 8

May 29 2024 51 mins

Erick Scott is founder of cStructure, a causal science startup. Erick has expertise in medicine, public health, and computational biology. [email protected] “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

Friends Let Friends Do Mediation Analysis with Nima Hejazi | Season 5 Episode 7

May 16 2024 59 mins

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?

Fun and Game(s) Theory with Aaditya Ramdas | Season 5 Episode 6

May 01 2024 48 mins

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 int

Cookies, Causal Inference, and Careers with Ingrid Giesinger #Epicookiechallenge | Season 5 Episode 5

Apr 17 2024 46 mins

Ingrid is a doctoral student in Epidemiology at the Dalla Lana School of Public Health at the University of Toronto. Winning cookie recipe Follow along on Twitter: The American Journal of Epidemiology: @AmJEpi Ellie: @EpiEllie Lucy: @LucyStats 🎶 Our intro/outro music is courtesy of Joseph McDadeEdited by Cameron Bopp