70 episodios
Regression to the Mean Girls | The Work is Mysterious and Important: Severance Data
07/09/2026 | 42 minFollow 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:
@regressiontothemeangirlsRegression to the Mean Girls | Romance by the Numbers: First Sparks Across Tropes
31/08/2026 | 56 minSarah 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/- 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. Combining Data & Making Effects Generalizable with Carly Brantner | Season 6 Episode 7
17/06/2025 | 52 minCarly 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.- 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.
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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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