The other hot new (ok ok old) thing is causal graphs. There’s still not enough guidance on how *exactly* to make your causal graph. In two new papers, we explored how well different expertise-based and computational approaches do (and don’t) work. Expertise: www.ncbi.nlm.nih.gov/pmc/articles...
Causal graphs are an important tool for covariate selection but there is limited applied research on how best to create them. Here, we used data from the Coronary Drug Project trial to assess a range ...
The hot new thing in causal inference is emulating a target trial, but how *exactly* do we do that? In a new paper led by Dr Julia Bond, we outline the steps and thought process for creating a target trial emulation. Now available here: onlinelibrary.wiley.com/action/oidcS...
Background The target trial framework was developed as a strategy to design and analyze observational epidemiologic studies with the aim of reducing bias due to analytic decisions. It involves desig...
Thanks for the starter pack recs, y’all (although I think my following list still needs more diversification!). I’m gonna try & be around more, but no promises — I have a herniated disc in my neck & compressed nerve and pain really seems to crush my creativity😔😔
Okay, I’m thinking to give this place more of a real try but who should I be following to get a good mix of backgrounds, content type, perspectives, etc? Because right now my feed is all work & no play. And also, let’s be honest, pretty much just full of white people 😬
Interested in the latest quasi-experimental difference-in-differences policy evaluation methods but not sure where to start? Our new tutorial in Epidemiology is out now with detailed info for beginners! journals.lww.com/epidem/abstr...#episky#econsky@justinwhite.bsky.social@epiellie.bsky.social
Sometimes, friends *do* let friends do mediation — but ONLY if they listen to this week’s Casual Inference podcast first!
🎙️ Our next episode is out! Analyzing the analysts: reproducibility with Nick Huntington-Klein! Lucy was out this week, but Nick and I have a great chat about how results vary when different analysts try to answer the same question using the same data! The answer may (or may not 😂) surprise you!
I am on the most recent episode of the Casual Inference podcast with @epiellie.bsky.socialcasualinfer.libsyn.com/analyzing-th...
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 ...
Curious to learn more about epidemiology? You’re in luck! Our book is coming soon to a bookstore near you 🥳🥳 More info here: global.oup.com/academic/pro...
It’s that time again! Another new episode of your favorite podcast🥳🥳 This week Lucy and I talk about immortal time bias, the clone-censor-weight approach to avoiding it, and an example of thinking through this bias in pregnancy research. Enjoy!
