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Joint Initiative for Causal Inference Webinar

October 26October 30

Logos for University of Copenhagen, Novo Nordisk, and UC Berkeley

We are happy to announce the inaugural Joint Initiative for Causal Inference Webinar. Join us from 7-9 am PDT (4-6 pm CEST) on October 26th, 28th, 30th for a series of presentations on utilizing causal inference and targeted learning methods to answer pressing health questions in the modern methodological and data ecosystem. Targeted learning methods bring the rigor and power of classical statistics and causal inference together with advances in machine learning to bring robust insight and evidence to the important health challenges. This program is organized by the University of California, Berkeley’s Center for Targeted Learning, Copenhagen University, and Novo Nordisk, a leading global healthcare company headquartered in Denmark.

Confirmed speakers: Dr. Maya Peterson (UC Berkeley), Dr. Mark van der Laan (UC Berkeley), Dr. Henrik Ravn (Novo Nordisk), Dr. Theis Lange (University of Copenhagen), Dr. Helene Rytgaard (University of Copenhagen), David Chen (UC Berkeley)

Each of the three days focuses on material targeted to audiences with a different level of expertise with statistical methodologies, from clinicians to data scientists.

Day 1 (primary audience is a general audience with an interest in the future of trials and real-world evidence generation): covers motivations for causal inference methodologies, an introduction to the causal inference roadmap, a series of applied uses of targeted learning methods, and highly relevant clinical examples that motivate new methods development.

Day 2 (primary audience is statisticians and computation experts with no prior knowledge of targeted maximum likelihood estimation [TMLE]): Hands-on case studies of the targeted maximum likelihood estimation of survival and point treatment parameters in randomized control trials.

Day 3 (primary audience is statistician and computation experts with interest in the use of TMLE for more complex questions): The third day will use a case study of HIV analysis to explore a range of more advanced questions that can be addressed using TMLE, including addressing intercurrent events, and evaluating the effects of longitudinal and dynamic (or personalized) treatments.

The webinar is free to attend and registration is capped at 1000.

To register, please click the “Enroll” button and complete the registration form.  You will be notified once the event site is available (coming soon!).  The event site will include an agenda, schedule, Zoom links, presentation information, session recordings and learning resources.