Here is the link to the book mentioned during the #Nutrition2023 American Society for Nutrition Causal Inference in Nutrition session: #CausalInference: What If (the book) Miguel Hernán hsph.harvard.edu/miguel-hernan/…

This month's ROSA SCORE Seminar takes place tomorrow, Wednesday, October 11th at 12PM. Speaker Jorge Chavarro, ScD, MD will discuss "Reproductive traits and adverse pregnancy outcomes as windows to overall health". Register here: partners.zoom.us/webinar/regist…

I am deeply honored and equally excited that I will soon join Harvard T.H. Chan School of Public Health as the next Dean there! Well… that’s the news. Advise, support, and cheering are all welcome ☺️ news.harvard.edu/gazette/story/…

Congrats to CAUSALab's Director Miguel Hernán for being awarded APHA's 2023 Lowell Reed Award! This award recognizes Miguel Hernán's groundbreaking work in the field of #causalinference & his contribution to shaping #healthpolicy & #research #methodology worldwide.

"Draw your assumptions before your conclusions" 5 years ago we launched the *free* #CausalDiagrams course Harvard Online @edxOnline. Since then, 80,000 people in 180 countries have registered. Check it out if you want to learn about DAGs and SWIGs : edx.org/learn/data-ana…

Check out our new paper in Nov issue of Am J Epidemiology! "Evaluating Model Specification When Using the Parametric G-Formula in the Presence of Censoring" Led by CAUSALab research collaborator Han Chiu and funded by NIH. Learn more👉bit.ly/3pxpSIR. #gformula

We're hosting a symposium Mar 6 (in-person Brigham and Women's Hospital & virtual) to bring you a line-up of brilliant nutrition colleagues & epidemiologists to discuss methods and works in progress addressing some of diet research's biggest challenges. To register: nutrition.bwh.harvard.edu

Our new paper on JAMA delineates the current effect score analyses--how to use CATE to characterize HTE in RCTs. We are on our way to develop effect score analyses for survival outcomes and other settings. jamanetwork.com/journals/jama/…

My lab is hiring a post-doctoral fellow. If you are interested in working with big data, pregnancy, childhood, and climate, please apply! jobs.rutgers.edu/postings/227307

A blanket ban on the use of causal language in observational studies has long precluded nuanced discussion about which associations, if any, are truly causal   Fantastic work by Issa Dahabreh (CAUSALab BIDMC Smith Center) and Kirsten Bibbins-Domingo changes this jamanetwork.com/journals/jama/…

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.

New research published Annals of Int Med challenges past scholarship on #metformin. CAUSALab research collaborator Han Chiu identified no increased risk for childbirth with major birth defects when compared w/ women who discontinued the drug. CNN article: cnn.com/2024/06/17/hea…

We developed an estimator to improve the efficiency of RCTs by integrating extetnal controls, which is consistent even if the transportability assumption does NOT hold. Pharmas can finally use the external control worry-free! arxiv.org/abs/2406.17971

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

Glad to see our efforts in print! 🙌Daniel Ibsen Martín Lajous Han Chiu Dalia Stern, Conor MacDonald

🎉 Excited to share that my NIH R35 grant on causal inference methods for treatment heterogeneity has been funded! Grateful for the support from my mentors and colleagues! 🙌 NIGMS Penn State News Penn State Health #CausalInference

Excited to share that our paper on a foundation AI model for cancer prognosis and pathology diagnosis is published in Nature today. nature.com/articles/s4158… DBMI at Harvard Med NIH NIGMS CDMRP American Cancer Society #AI #DigitalPathology

CAUSALab Director Miguel Hernán delivered the keynote, “Causal inference and Al. What can we learn from data and how much learning can we automate?" today at ACE 2024 Annual Meeting. Dr. Hernán introduced this year’s focus on AI & epidemiological research ACE. #causal