Cookies, Causal Inference, and Careers with Ingrid Giesinger #Epicookiechallenge | Season 5 Episode 5
Casual Inference
Ingrid is a doctoral student in Epidemiology at the Dalla Lana School of Public Health at the University of Toronto. Follow along on Twitter: The American Journal of Epidemiology: Ellie: Lucy: 🎶 Our intro/outro music is courtesy of Edited by
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Analyzing the Analysts: Reproducibility with Nick Huntington-Klein | Season 5 Episode 4
Casual Inference
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: The Paper of How: Nick’s twitter & BlueSky: @nickchk Nick’s website: Follow along on Twitter: The American Journal of Epidemiology: ...
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Immortal Time Bias | Season 5 Episode 3
Casual Inference
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: Immortal time in pregnancy: Follow along on Twitter: The American Journal of Epidemiology: Ellie: Lucy: 🎶 Our intro/outro music is courtesy of Edited by
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Targeted Learning with Mar van der Laan | Season 5 Episode 2
Casual Inference
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 Learning, Berkeley: A causal roadmap: Short course on causal learning: Handbook on the TLverse (Targeted Learning in R): Mark on twitter: Follow along on Twitter: The American...
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Pros and Cons of Randomized Controlled Trials | Season 5 Episode 1
Casual Inference
Ellie and Lucy kick off the season and introduce our new executive buzzer, Melita! Melita is a masters student in statistics at Wake Forest University and will be helping out with the podcast (and keeping Lucy and Ellie from using too much jargon!) Pros & Cons of RCT paper: Fernainy, P., Cohen, A.A., Murray, E. et al. Rethinking the pros and cons of randomized controlled trials and observational studies in the era of big data and advanced methods: a panel discussion. BMC Proc 18 (Suppl 2), 1 (2024). Follow along on Twitter: The American Journal of Epidemiology: Ellie: ...
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Remembering Ralph B. D'Agostino, Sr.
Casual Inference
We are re-releasing an episode from 2021 in remembrance of . Ellie Murray and Lucy D’Agostino McGowan chat with Ralph D’Agostino Sr. and Ralph D’Agostino Jr. about their careers in statistics, looking back at how things have developed and forward at where they see the world of statistics and epidemiology going. Ralph D’Agostino Sr. was a professor of Mathematics/Statistics, Biostatistics, and Epidemiology at Boston University. He was the lead biostatistician for the Framingham Heart Study, a biostatistical consultant to The New England Journal of Medicine, an editor of...
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Evidence Science with Cat Hicks | Season 4 Episode 11
Casual Inference
Ellie and Lucy chat with Dr. Cat Hicks, VP of Research Insights and at Pluralsight Flow, about evidence science. Follow along on Twitter: Cat: The American Journal of Epidemiology: Ellie: Lucy: 🎶 Our intro/outro music is courtesy of Edited by Quinn Rose:
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M-Bias: Much Ado About Nothing? | Season 4 Episode 10
Casual Inference
Lucy D'Agostino McGowan and Ellie Murray chat about a "Causal Quartet" and spend some extra time on M-Bias! Follow along on Twitter: The American Journal of Epidemiology: Ellie: Lucy: 🎶 Our intro/outro music is courtesy of Edited by Quinn Rose:
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Thinking about Targeted Learning | Season 4 Episode 9
Casual Inference
Lucy D'Agostino McGowan and Ellie Murray chat about ENAR 2023 and Targeted Learning! Follow along on Twitter: The American Journal of Epidemiology: Ellie: Lucy: 🎶 Our intro/outro music is courtesy of Edited by Quinn Rose:
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Prevention Strategies via the #Epicookiechallenge | Season 4 Episode 8
Casual Inference
Lucy D'Agostino McGowan and Ellie Murray chat with #EpiCookieChallenge winner, Viktoria Gastens! Follow along on Twitter: The American Journal of Epidemiology: Viktoria: Viktoria's Lab: Ellie: Lucy: 🎶 Our intro/outro music is courtesy of Edited by Quinn Rose:
info_outlineIn this episode Lucy D'Agostino McGowan and Ellie Murray chat with Noah Haber about metascience, causal language in the literature, and more!
🥇 Causal Inference Nobel Prize Press Release
đź“ť What Should Researchers Expect When They Replicate Studies? A Statistical View of Replicability in Psychological Science
đź“ť Design principles of data analysis
đź“ť Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review
đź”— Reading past headlines [part 1]
đź”— Reading past headlines [part 2]
Follow along on Twitter:
- Noah: @NoahHaber
- The American Journal of Epidemiology: @AmJEpi
- Ellie: @EpiEllie
- Lucy: @LucyStats
🎶 Our intro/outro music is courtesy of Joseph McDade.