¡Bienvenido Miguel Hernán! A full room at Sydney School of Public Health [Sydney Health] welcoming Miguel at University of Sydney 🌏🦘🐨🪃🇦🇺. Pleased to have you with us!

Love this - I have never understood grant reviewer demands for hypotheses to be added to clearly stated research questions (or the condescension with which such demands are often made) If a ? is an open empirical one that could go either way, why would you have a hypothesis?

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In other words, your hypothesis is nobody's business.

Student tuition waiver applications are now open for our 2024 courses on #causalinference! This summer, we offer four unique courses led by academic experts in the field Harvard T.H. Chan School of Public Health. Course registration will open in early February ⏰ Learn more 👉 causalab.sph.harvard.edu/courses

I study causal informatics. Period. Thanks Miguel Hernán for making my future self-introduction so much easier, and for a great keynote talk with successes and failures towards reliable RWE! #IS24 #AMIA

Exciting news! CAUSALab has partnered with CEMFI Summer School for a NEW course taught by Miguel Hernán “Causal Inference for Health and Social Scientists” covers a 2-step #causal framework. Applications due June 14, 2024 📅8/26-8/30 📍Madrid Learn more: cemfi.es/programs/css/c…

With #TargetTrial emulation becoming increasingly popular, it's important to understand what it can and cannot do. In this new podcast, I discuss how target trial emulation can 1) improve causal inference from observational data, and 2) extend inferences from randomized trials.

The 2024 CAUSALab Summer Courses have officially begun 🎉 We are thrilled to welcome attendees from around the world and across various organizations. Here’s to an incredible two weeks of learning! #2024CAUSALabcourses

Did you know that the LATE estimator was independently described in 1994 by Imbens & Angrist in Econometrica (Econometrica) and Baker & Lindeman in Statistics in Medicine? onlinelibrary.wiley.com/doi/10.1002/si… A delightful historical overview of LATE is now available tandfonline.com/doi/full/10.10…

The TARGET Reporting Guideline team needs your help. If you work on #causalinference from observational data, please get involved in piloting the reporting guidelines for #TargetTrial emulation. Diverse viewpoints will make the guidelines more useful for everyone in #RWE. More info👇

I was afraid my origin story would be revealed eventually…

This week I discussed methods for health technology assessment HTAi: "Observational data (#RWD) can often be used to emulate a #TargetTrial, but we need more research to characterize questions that can only be answered by randomized trials." Let's learn the limits of #RWE

That👇should be the most comprehensive lesson-learned from the #covid19 pandemic. And people have to accept that politics makes also wrong decisions under these conditions. But somtimes it is even worse to do nothing. And retrospectively one is always smarter. Thx Miguel Hernán

See Dr. Miguel Hernan present at the Conference on Big Data in Biomedical and Population Health Sciences. Miguel Hernan, MD, DrPH, (Miguel Hernán) is the Director of the CAUSALab (CAUSALab) at Harvard T.H. Chan School of Public Health (Harvard T.H. Chan School of Public Health). bit.ly/PennBigData2024

Biden stutters. So do I. At the debate, he froze, appeared to lose his train of thought, and tripped over his words. Every stutterer knows how embarrassing this is: people feel uneasy and think you're an idiot. But acumen and speech fluency are separate things, as we all saw.

We aim to build opportunities for accessible #causalinference research. CAUSALab awarded 42 tuition waivers for students to join us for #2024CAUSALabcourses! Recipients represented: 🎓 25 institutions 🌎 13 countries 📍 7 US states Congrats to this year's cohort!

In this Friday's PCT Grand Rounds, Miguel Hernán of CAUSALab at Harvard T.H. Chan School of Public Health discusses causal estimands and asks whether we should be posing different causal questions in randomized trials. Join us! #biostatistics #pctGR ➡️ duke.is/pctgr20240712