Causal Mediation Analysis Training: Methods and Applications Using Health Data COVID-19 Update: The Causal Mediation Analysis Training will no longer take place in person due to the COVID-19 pandemic. The Training will instead be a live-stream, remote training that takes place over live, online video on August 12-14, 2020 from 10am EDT – 5pm EDT. Please note this training is not a self-paced, pre-recorded online training. The Causal Mediation Analysis Training is a 3-day intensive boot camp of seminars and hands-on analytical sessions to provide an overview of concepts and data analysis methods used to investigate mediating mechanisms. KEYNOTE SPEAKER Kosuke Imai, PhD, Harvard University. INSTRUCTORS Linda Valeri, PhD, Mailman School of Public Health, Columbia University. Caleb Miles, PhD, Mailman School of Public Health, Columbia University. Investigators at all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. PREREQUISITES AND REQUIREMENTS 1. Each participant must be familiar with linear and logistic regression. 2. Each participant must have experience with programming in SAS and/or R. 3. Although the instructors will provide an overview of the fundamentals of causal inference (potential outcomes, directed acyclic graphs, and marginal structural models), we invite the participants to read chapters 1-7, 11, and 12 of Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC (free). 4. Each participant is required to bring a personal laptop with R/RStudio installed prior to the first day of the workshop, as all lab sessions will be done on your personal laptop. R is available for free download and installation on Mac, PC, and Linux devices. You will receive a SAS/Stata license for the duration of the training. For more details and to subscribe for updates, email us at Columbia.CMA@gmail.com Website: mailman.columbia.edu/Causal-Mediation Capacity is limited. Paid registration is required to attend.