“Estimation and interpretation: introduction to parametric and semi-parametric estimators for causal inference”
February 9, 2018
9:00am – 2:00pm
UCLA School of Public Health
650 Charles E. Young Dr. South
Center for Health Sciences
Room: 53-105 CHS
Los Angeles, CA 90095
Campus map, parking, and
transportation details, click here.
Schedule Breakdown:
This workshop will introduce participants to a “causal roadmap” approach to epidemiologic questions: 1) clear statement of the scientific question, 2) definition of the causal model and parameter of interest, 3) assessment of identifiability – that is, linking the causal effect to a parameter estimable from the observed data distribution, 4) choice and implementation of estimators including parametric and semi-parametric, and 5) interpretation of findings. The focus will be on estimation with a simple substitution estimator (parametric g-computation), inverse probability of treatment weighting (IPTW), and targeted maximum likelihood estimation (TMLE) with Super Learner. Participants will work through the roadmap using an applied example and implement these estimators in R during the workshop session.