Skip to content
Sign in
Artwork for Casual Inference
ScienceMathematics

Casual Inference

Lucy D'Agostino McGowan and Ellie Murray

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.

Play
Open in
  • 24 episodes
  • Avg 49 min
  • English

Episodes 24

NewestOldestLongest
All20Unplayed20In progress0Played0
Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.
  • S1 · E4
    Monday · 39 min

    Regression to the Mean Girls | The Art of Web Scraping Art with Hadley Wickham

    Follow Regression to the Mean Girls on [⁠⁠Apple Podcasts⁠⁠], [⁠⁠Spotify⁠⁠], or wherever you love to listen! ⁠Hadley Wickham⁠ (Posit) joins ⁠⁠⁠⁠⁠Sarah Lotspeich⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠Lucy D'Agostino McGowan⁠⁠⁠⁠⁠⁠ with a data-driven side quest into building a web scraper to help acquire art. Check out the full process here: ⁠⁠⁠⁠⁠regressiontothemeangirls.com⁠⁠⁠⁠⁠ Links to content we chat about on the episode: ⁠⁠⁠Weston Lambert Art⁠ ⁠Parallel strands between learning crochet and learning programming by Maëlle Salmon⁠ Follow along on instagram: ⁠⁠⁠@regressiontothemeangirls⁠

  • September 14 · 1 hr 13 min

    Regression to the Mean Girls | The Comfort of Competence and the Speed of Justice, According to Law & Order

    Follow Regression to the Mean Girls on [⁠Apple Podcasts⁠], [⁠Spotify⁠], or wherever you love to listen! Christine Zhang⁠ (⁠New York Times⁠) joins ⁠⁠⁠Sarah Lotspeich⁠⁠⁠ and ⁠⁠⁠Lucy D'Agostino McGowan⁠⁠⁠⁠ with a data-driven side quest into the TV show Law and Order. Check out the full analysis here: ⁠⁠⁠regressiontothemeangirls.com⁠⁠⁠ Links to content we chat about on the episode: ⁠Wrong Number newsletter⁠ ⁠The Speed of Justice, According to Law & Order⁠ Follow along on instagram: ⁠@regressiontothemeangirls

  • S1 · E2
    September 7 · 42 min

    Regression to the Mean Girls | The Work is Mysterious and Important: Severance Data

    Follow Regression to the Mean Girls on [Apple Podcasts], [Spotify], or wherever you love to listen! ⁠Lucy D'Agostino McGowan⁠⁠ and ⁠⁠Sarah Lotspeich⁠⁠ return with a data-driven side quest into the TV show Severance. Lucy analyzes whether Milchick really uses more complicated language than his colleagues. Check out the full analysis here: ⁠⁠regressiontothemeangirls.com⁠⁠ Links to content we chat about on the episode: ⁠⁠Lucy's Severance data R package [mdr]⁠⁠ ⁠⁠Lucy's other Severance analyses⁠⁠ ⁠⁠Dunnet⁠⁠ ⁠⁠Radial plot of who is speaking in Severance ⁠⁠ Follow along on instagram: @regressiontothemeangirls

  • August 31 · 56 min

    Regression to the Mean Girls | Romance by the Numbers: First Sparks Across Tropes

    Sarah Lotspeich⁠ and ⁠Lucy D'Agostino McGowan⁠ introduce Regression to the Mean Girls, a podcast about data-driven side quests in pop culture. In this episode, Sarah analyzes 45 recent romance novels to find out how different romance tropes affect the timing of the couple’s first kiss. Check out the full analysis here: ⁠https://regressiontothemeangirls.com/⁠ Links to content we chat about on the episode: ⁠Edward L. Kaplan and the Kaplan-Meier Survival Curve⁠ ⁠Nonparametric Estimation from Incomplete Observations⁠ ⁠Not just love, actually: why romance fiction is booming⁠ ⁠What is the lipstick index?⁠ Follow along on instagram: @regressiontothemeansgirls Podcast feed: https://creators.spotify.com/pod/profile/rttmg/

  • Jun 26, 2025 · 52 min

    Optimizing Data Workflows with Emily Riederer | Season 6 Episode 8

    Emily Riederer is a Data Science Senior Manager at Credit Risk Modeling Capital One. Her website can be found here: https://www.emilyriederer.com/ Follow along on Bluesky: Emily: ‪@emilyriederer.bsky.social‬ Ellie: @epiellie.bsky.social Lucy: @lucystats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.

  • Jun 17, 2025 · 52 min

    Combining Data & Making Effects Generalizable with Carly Brantner | Season 6 Episode 7

    Carly Brantner is an assistant professor of Biostatistics & Bioinformatics at Duke University and Duke Clinical Research Institute. Resources from this episode: multicate: R package for estimating conditional average treatment effects across one or more studies using machine learning methods PCORnet® Front Door: Access point for potential investigators, patient groups, and other stakeholders to connect with PCORnet and get support for potential research studies Patient-Centered Outcomes Data Repository (PDOCR): De-identified data from 24 (and counting) PCORI-funded studies Follow along on Bluesky: Carly: @carlybrantner.bsky.social Ellie: @epiellie.bsky.social Lucy: @lucystats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.

  • May 29, 2025 · 49 min

    The Art of Clarity with Andrew Heiss | Season 6 Episode 6

    Andrew Heiss is an assistant professor in the Department of Public Management and Policy at the Andrew Young School of Policy Studies at Georgia State University. Vincent's "What is your estimand" section in his {marginaleffects} book: https://marginaleffects.com/chapters/challenge.html#sec-goals_estimand Article on defining estimands: https://doi.org/10.1177/00031224211004187 Andrew's marginal effects post: https://www.andrewheiss.com/blog/2022/05/20/marginalia/ Andrew's post on "fixed effects" and mariginal effects across different disciplines: https://www.andrewheiss.com/blog/2022/11/29/conditional-marginal-marginaleffects/ Follow along on Bluesky: Andrew: @andrew.heiss.phd Ellie: @epiellie.bsky.social Lucy: @lucystats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.

  • May 8, 2025 · 55 min

    Study Critique: What Went Wrong and How We'd Do It Differently | Season 6 Episode 5

    In this episode Lucy and Ellie dig into a recently publicized paper, "Vaccination and Neurodevelopmental Disorders: A Study of Nine-Year-Old Children Enrolled in Medicaid", which has gained attention after being promoted by RFK Jr. as evidence that vaccines cause autism. Ellie breaks down her Substack critique of the study. Together, she and Lucy discuss the methodological flaws and what a better version of this study might look like. Vaccination and Neurodevelopmental Disorders: A Study of Nine-Year-Old Children Enrolled in Medicaid: https://publichealthpolicyjournal.com/vaccination-and-neurodevelopmental-disorders-a-study-of-nine-year-old-children-enrolled-in-medicaid/ RFK Jr is promoting a new study claiming "vaccines cause autism" but it doesn't add up. Literally [Ellie's substack]: https://epiellie.substack.com/p/rfk-jr-is-promoting-a-new-study-claiming Follow along on Bluesky: Ellie: @epiellie.bsky.social Lucy: @lucystats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.

  • Apr 24, 2025 · 45 min

    From Model to Meaning with Vincent Arel-Bundock | Season 6 Episode 4

    Vincent Arel-Bundock is a professor at the Université de Montréal, where he studies comparative and international political economy. Vincent's website: https://arelbundock.com/ Vincent's book "Model to Meaning: How to Interpret Statistical Models With marginaleffects for R and Python": https://marginaleffects.com/ Follow along on Bluesky: Vincent: @vincentab.bsky.social Ellie: @epiellie.bsky.social Lucy: @lucystats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.

  • Apr 10, 2025 · 1 hr 22 min

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

    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: @LucyStats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade. Edited by Cameron Bopp.

  • Mar 27, 2025 · 51 min

    Causal Assumptions and Large Language Models | Season 6 Episode 2

    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.

  • Feb 28, 2025 · 44 min

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

    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.bsky.social Ellie: @EpiEllie.bsky.social Lucy: @LucyStats.bsky.social 🎶 Our intro/outro music is courtesy of Joseph McDade

  • Jul 10, 2024 · 48 min

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

    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

  • Jun 26, 2024 · 38 min

    Flexible methods with Edward Kennedy | Season 5 Episode 10

    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

  • Jun 12, 2024 · 49 min

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

    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

  • May 29, 2024 · 51 min

    Observational Causal Analyses with Erick Scott | Season 5 Episode 8

    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

  • May 16, 2024 · 59 min

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

    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

  • May 1, 2024 · 48 min

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

    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

  • Apr 3, 2024 · 45 min

    Analyzing the Analysts: Reproducibility with Nick Huntington-Klein | Season 5 Episode 4

    Nick Huntington-Klein is an Assistant Professor, Department of Economics, Albers School of Business and Economics, Seattle University. His research focus is econometrics, causal inference, and higher education policy. He's also the author of an introductory causal inference textbook called The Effect and the creator of a number of Stata packages for implementing causal effect estimation procedures. Nick's book, online version: https://theeffectbook.net/ The Paper of How: https://onlinelibrary.wiley.com/share/W2FMEESMMSJMWDEZYY8Y?target=10.1111/obes.12598 Nick's twitter & BlueSky: @nickchk Nick's website: https://nickchk.com 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

Showing 1–20 of 24 episodes