Centers of Excellence


Center for Causal Inference



The Center for Causal Inference had its third annual Causal Inference Summer Institute, a three-day, intensive learning experience that took place at the Rutgers University campus in New Brunswick, NJ. 

Each day offered didactic lectures by experts in the field, discussion of real examples, and hands-on computing sessions. The opening day featured an inaugural Distinguished Lectureship by James Robins(link is external), MD, Mitchell L. and Robin LaFoley Dong Professor of Epidemiology at the Harvard T.H. Chan School of Public Health.

The final day featured new ideas on designing and analyzing pharmocoepidemiology studies using causal approaches.

Statisticians, epidemiologists, clinicians, and researchers from other disciplines  interested in gaining an understanding and practical foundation in causal inference were welcomed.

Causal Day 1 (Wednesday, July 10)

Time Event Presenter
8:00-8:30am Registration; Light breakfast  
8:30-8:45am Welcome and overview Jason Roy
8:45-10:15am Introduction to causal inference: potential outcomes / counterfactuals; DAGs / confounding; causal assumptions Andrew Spieker
10:15-10:30am Break  
10:30-12:00pm Estimation of treatment effects: matching; propensity scores; inverse probability of treatment weighting Luke Keele
12:00-1:30pm Lunch (on your own)  
1:30-2:45pm Computer session on estimation of treatment effects Ted Westling
2:45-3:00pm Break  
3:00-4:00pm Sensitivity analysis Dylan Small
4:00-5:00pm Reception: hors d'oeuvres  
5:00-5:15pm Opening remarks   
5:15-6:15pm Distinguished Lectureship James Robins

Causal Day 2 (Thursday, July 11)

Time Event Presenter
8:00-8:30am Registration; Light breakfast  
8:30-8:45am Welcome and overview  
8:45-9:45am Instrumental variables Nandita Mitra
9:45-10:30am Computing session on IV Arman Oganisian
10:30-10:45am Break  
10:45-11:45am Difference-in-differences Bret Zeldow
11:45pm-1:00pm Lunch (on your own)  
1:00-2:00pm Causal mediation analysis Donna Coffman
2:00-3:00pm Overview of time-dependent confounding: DAGs; causal assumptions; g-methods Jason Roy
3:00-3:15pm Break  
3:15-4:15pm Marginal structural models Peter Yang
4:15-5:30pm Double robustness and machine learning in causal inference Edward Kennedy


Pharmacoepidemiology (Friday, July 12)

Time Event Presenter
8:00-8:45am Registration; Light breakfast  
8:45-9:00am Welcome and overview  
9:00-9:30am Emerging topics vs. standards in the field – a matter of perspective Brian Strom
9:30-10:45am The trend-in-trend research design Sean Hennessy
10:45am-11:15am Break  
11:15am-12:15pm Pharmacoepidemiology and the microbiome Daniel Horton
12:15-1:30pm Lunch (on your own)  
1:30-2:30pm Mendelian randomization: methods and application to heart disease prevention QIngyuan Zhao

Weather-drug interactions, part 1: ambient temperature and the survival benefit of potassium in furosemide users and of statins

Sean Hennessy
3:15-4:00pm Weather-drug interactions, part 2: heat-related outcomes and medication use in older adults with chronic diseases Soko Setoguchi


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About CCI

The Center for Causal Inference (CCI) is a research center that is operating under a partnership between Penn’s Center for Clinical Epidemiology and Biostatistics (CCEB), the Department of Biostatistics and Epidemiology, Rutgers School of Public Health, and Penn’s Wharton School. The mission of the CCI is to be a leading center for research and training in the development and application of causal inference theory and methods.

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