Full course description
We are pleased to announce the Spring 2021 Joint Initiative for Causal Inference Webinar Series. Join us from 7-9 am PST/PDT (4-6 pm CET/CEST) on the first Wednesdays of the month (March - June 2021) 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 Machine Learning, University of Copenhagen, and Novo Nordisk, a leading global healthcare company headquartered in Denmark. The talks will range from those targeted at a general audience with an interest in the future of trials and real-world evidence generation to statisticians and data scientists working at or interested in the intersection of causal inference, machine learning, and statistics.
Confirmed speakers: Dr. Maya Petersen (UC Berkeley), Dr. Mark van der Laan (UC Berkeley), Dr. Theis Lange (University of Copenhagen), Dr. Helene Rytgaard (University of Copenhagen), Dr. Søren Rasmussen (Novo Nordisk), David Chen (UC Berkeley), Dr. Zeyi Wang (UC Berkeley), Lauren Eyler (UC Berkeley), Dr. Andrew Mertens (UC Berkeley)...and others to be announced.
Session 1 - Wednesday, March 3rd
After an introduction to challenges posed by competing risks from both an industry and academic perspective, David Chen will present on current methods and problems in handling competing risks, including discrete-time targeted maximum likelihood estimation results from simulations and analysis of the LEADER trial. The second presentation, by Dr. Helene Rytgaard, will discuss novel methods for competing risks: continuous time and 1-step targeted maximum likelihood estimation, as well as applications.
Session 2 - Wednesday, April 7th
A series of three presentations of methodological developments in longitudinal mediation analysis and clinical applications from Drs Theis Lange, Søren Rasmussen, and Zeyi Wang. After an introduction from Dr. Maya Petersen (5 min.), Dr. Theis Lange will present ”How are epidemiologists working with current mediation tools? Stories from the front” (20 min.). This talk will cover challenges and practical obstacles in ongoing mediation analyses that the JICI hopes to solve. Then, Dr. Søren Rasmussen will present on a Novo Nordisk-led mediation analysis of the Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results (LEADER) trial (20 min.). Lastly, Dr. Zeyi Wang will present methodological advances in targeted-learning approaches to longitudinal mediation, with simulations and application to LEADER data (35 min.), followed by a question and answer session for all three talks (40 min.).
Session 3 - Wednesday, May 5th
An overview of methods for the integration of observational and randomized control trial data. Speakers TBA
Session 4 - Wednesday, June 2nd
Applications of the causal inference roadmap to diabetes-dementia dynamics using Danish health registry and randomized control trial data. Speakers TBA
The webinar is free to attend.
To register, please click the "Enroll" button and complete the registration form. After enrolling, you will have access to the event site, including the schedule, Zoom links, presentation information, session recordings, learning resources and archives of past webinars. If you have any trouble with registration, please send an email to firstname.lastname@example.org and we will manually enroll you in the event site.
If you require an accommodation for effective communication (ASL interpreting/CART captioning, alternative media formats, etc.) to fully participate in this event, please contact Lucas Carlton at email@example.com with as much advance notice as possible in advance of the event.