Centers of Excellence


Center for Causal Inference

Causality in Clinical Research: What, Why, When & How

Causality in Clinical Research: What, Why, When & How

The Center for Causal Inference is pleased to announce a virtual short course that will provide a non-technical introduction to concepts in causality.  

Registration is now CLOSED.

Program Overview & Target Audience
In just two half-days on December 3 & 4, starting at 9 a.m. and ending at 1 p.m ET., top experts from Penn, Rutgers, Johns Hopkins, and Vanderbilt will teach a variety of fundamental topics in causal inference including propensity score matching and weighting, instrumental variables, difference-in-differences study designs, and machine learning approaches.  All methods will be illustrated using real clinical examples.  

The course will be specifically aimed towards clinical researchers who have a basic understanding of statistics, but who perhaps have not had formal training in causal inference concepts and methods. 

Learning Objectives
Upon completing this activity, learners should be able to:

  • Review the history of causality in the context of clinical research
  • Explain the difference between association versus causation
  • Describe various observational study designs
  • Apply analytical strategies for measured and unmeasured confounding

Two-day Agenda

December 3

Time Title Presenter
9:00-9:10 am Opening Remarks and Introductions Nandita Mitra, PhD
University of Pennsylvania
9:10-9:50 am A Brief History of Causality Elizabeth Ogburn, PhD
Johns Hopkins University
10:00-11:20 am

An introduction to causal concepts: Potential outcomes, DAGs, confounding

Alisa Stephens-Shields, PhD
University of Pennsylvania

11:30-1:00 pm Propensity scores: matching, weighting Andrew Spieker, PhD
Vanderbilt University

December 4

Time Title Presenter
9:00-10:20 am Instrumental Variables and Unmeasured Confounding Nandita Mitra, PhD
University of Pennsylvania
10:30-11:30 am

Causal Study Designs: Difference-in-Differences and Regression Discontinuity

Luke Keele, PhD
University of Pennsylvania
11:40-1:00 pm Machine Learning Approaches to Causal Inference

Jason Roy, PhD
Rutgers University

Registration is CLOSED
Standard rate: $325
Trainee/student rate: $175

Once the course has started, no new participants will be accepted. You will receive the BlueJeans conference call information once your registration is complete and payment has been processed.   Please note that advance registration is required.

Questions? Contact Lisbeth Dennis.

In support of improving patient care, Penn Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.  

Designation of Credit 
Penn Medicine designates this live activity for a maximum of 7.25 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.  

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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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423 Guardian Drive 
Philadelphia, PA 19104 

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