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SERtalks – UCLA

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Laura Balzer
Assistant Professor
University of Massachusetts-Amherst
School of Public Health and Health Sciences

Jennifer Ahern
Associate Dean for Research
Associate Professor
University of California, Berkeley
School of Public Health

“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: 

09:00 am -10:30 am  – lecture
10:30 am -10:45 am  – break
10:45 am -12:15 pm  – lecture
12:15 pm -12:45 pm  – light lunch break
12:45 pm – 01:45 pm  – lecture

 

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.