Casual Inference

Jul 10 2024 60 ep. 58 mins 2.1k

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.

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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

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

Apr 03 2024 45 mins

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 est

Immortal Time Bias | Season 5 Episode 3

Mar 20 2024 34 mins

Lucy and Ellie chat about immortal time bias, discussing a new paper Ellie co-authored on clone-censor-weights. The Clone-Censor-Weight Method in Pharmacoepidemiologic Research: Foundations and Methodological Implementation: https://link.springer.com/article/10.1007/s40471-024-00346-2 Immortal time in pregnancy: https://pubmed.ncbi.nlm.nih.gov/36805380/ Follow along on Twi

Targeted Learning with Mar van der Laan | Season 5 Episode 2

Mar 06 2024 51 mins

Mark van der Laan is a professor of statistics at the University of California, Berkeley. His research focuses on developing statistical methods to estimate causal and non-causal parameters of interest, based on potentially complex and high dimensional data from randomized clinical trials or observational longitudinal studies, or from cross-sectional studies. Center for Targeted