
Casual Inference
Causal inference for data science with Sean Taylor | Episode 08
Feb 20, 2020 · 1 hr 29 min · 72.0 MB
0:00-1:29:46
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Ellie Murray and Lucy D'Agostino McGowan chat with Sean Taylor from Lyft.
Here are some links to the content we talk about in this episode:
📝 Sean's Science paper
📦 Prophet R package
📝 Book on time-varying exposures
📝 Lyft engineering blog
📝 Hormone replacement therapy overview
📝 Analyzing observational HRT data by emulating a trial
📰 Local news
- AJE Methods Corner
Follow along on Twitter:
- The American Journal of Epidemiology: @AmJEpi
- Ellie: @EpiEllie
- Lucy: @LucyStats
- Sean: @SeanJTaylor
🎶 Our intro/outro music is courtesy of Joseph McDade.
👩🎨 Our artwork is by Allison Horst.
Science paper
science.sciencemag.orgR package
cran.r-project.orgtime-varying exposures
hsph.harvard.edublog
eng.lyft.comoverview
journals.lww.comemulating a trial
ncbi.nlm.nih.govMethods Corner
academic.oup.com@AmJEpi
twitter.com@EpiEllie
twitter.com@LucyStats
twitter.com@SeanJTaylor
twitter.comJoseph McDade
josephmcdade.comAllison Horst
twitter.com