Due to the current circumstances, we have decided to cancel the fourth annual Causal Inference Summer Institute. We plan to hold the Summer Institute in June 2021.
The Center for Causal Inference is proud to announce its fourth annual Causal Inference Summer Institute, a four-day, intensive learning experience that will take place at the Jordan Medical Education Center 5th Floor Law Auditorium, 3400 Civic Center Blvd, Philadelphia, PA. Perelman School of Medicine, University of Pennsylvania.
Each day will offer didactic lectures by experts in the field, discussion of real examples, and hands-on computing sessions. This year, our opening day will feature a Distinguished Lectureship by Susan Murphy, Professor of Statistics, Harvard University.
Our fourth day will feature new ideas on designing and analyzing pharmocoepidemiology studies using causal approaches.
We welcome statisticians, epidemiologists, clinicians, and researchers from other disciplines who are interested in gaining an understanding and practical foundation in causal inference
SCHEDULE OVERVIEW (TENTATIVE)
- Introduction to Causal Inference Concepts: Causation versus Association and the Potential Outcomes Framework (Alisa Stephens-Shields)
- Propensity Scores and Inverse Probability Weighting (Andrew Spieker)
- Matching Approaches (Luke Keele)
- Workshop on Propensity Scores and Matching (Youjin Lee and Rahul Ladhania)
- Sensitivity Analysis (Dylan Small)
- Distinguished Lectureship Keynote Address (Susan Murphy)
- Unmeasured Confounding and Instrumental Variables (Nandita Mitra)
- Workshop on IVs (Hyunseung Kang)
- Difference-in-Differences (Bret Zeldow)
- Marginal Structural Models and Time Dependent Confounding (Ted Westling)
- Mediation Analysis (Donna Coffman)
- Mid-Career Award: Invited Lecture (Sherri Rose)
- Introduction to Bayesian Causal (Arman Oganisian)
- Bayesian Causal (Jason Roy)
- Bayesian Workshop (Arman Oganisian)
- Machine Learning (Jason Roy and Nandita Mitra)
- Machine Learning Workshop (Jason Roy)
Day 4: Pharmacoepidemiology Day
- Real World Data and Real World Evidence: What’s New Here? (Robert Reynolds)
- Using Human Sepsis Observational Data to Identify Potential Druggable Pathways (Nuala J. Meyer)
- Using Flatiron to Study the Real-world Effects of Cancer Treatments (Ronac Mamtani)
- Impact of Unmeasured Within- and Between-Cluster Confounding on Estimating the of Continuous Exposures (Yun Li)
- Using EHRs to Explore Heterogeneity of Drug Treatment Effect in Hospitalized Patients (Todd Miano)
- Medication Class Enrichment Analysis (MCEA): A Novel Way to Evaluate The Effects of Multiple Medications with a Disease of Interest, as applied to Clostridium difficile Infection (Ravy K. Vajravelu)
- Methods for the Analysis of Error Prone Data from Electronic Health Records (Pamela Shaw)
- Assessing Outcomes and Covariates in the EHR (Rebecca Hubbard)
- Accounting for Case Contamination in EHR-Based Case-Control Studies (Jinbo Chen)
- Studying the Real-world Effects of Medical Devices (Mary Beth Ritchey)
For a more detailed schedule, click here.
The Institute is sponsored by the CCI’s three cooperating institutions: 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 pharmacoepidemiology day is jointly organized by Rutgers Center for Pharmacoepidemiology and Treatment Science (PETS) and the Penn Center for Pharmacoepidemiology Research and Training (CPeRT).
For additional questions, please contact Lisbeth Dennis.