Location
This workshop was held at Penn Pavilion on the campus of Duke University.
Description
Causality is a subject at the frontier of academic debate over research methodology in a wide range of data-based disciplines including statistics, computer science, as well as in social and medical sciences. The “big data” era has brought unprecedented challenges and opportunities for causal inference. This SAMSI program aimed to advance causal inference research by bringing together leading mathematical, statistical, computational, and sciences researchers to pursue innovative methodology for causal inference and applications to important real-world problems.
Confirmed speakers for this event included:
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- Guillaume Basse (Stanford University)
- Mike Daniels (University of Florida)
- Tirthankar DasGupta (Rutgers University)
- Dean Eckles (MIT)
- Frederick Eberhardt (Caltech)
- Robin Evans (Oxford University)
- Avi Feller (University of California, Berkeley)
- Colin Fogarty (MIT)
- Laura Forastiere (Yale University)
- Beth Ann Griffin (RAND)
- Laura Hatfield (Harvard University)
- Luke Keele (University of Pennsylvania)
- Edward Kennedy (Carnegie Mellon University)
- Michael Kosorok (UNC-Chapel Hill)
- Michael Leung (University of Southern California)
- Jared Murray (University of Texas, Austin)
- Betsy Ogburn (Johns Hopkins University)
- Thomas Richardson (University of Washington)
- Michael Rosenblum (Johns Hopkins University)
- Cynthia Rudin (Duke University)
- Michael Sobel (Columbia University)
- Peter Spirtes (Carnegie Mellon University)
- Elizabeth Stuart (Johns Hopkins University)
- Eric Tchetgen Tchetgen (University of Pennsylvania, Wharton)
- Laine Thomas (Duke University)
- Carolina Uhler (MIT)
- Mark van der Laan (University of California, Berkeley)
- Stefan Wager (Stanford University)
- Lu Wang (University of Michigan)
- Yanxun Xu (Johns Hopkins University)
- Kun Zhang (Carnegie Mellon University)
- Qingyuan Zhao (University of Cambridge)
- Cory Zigler (University of Texas, Austin)
- Jose Zubizarreta (Harvard University)
Schedule and Supporting Media
Printed Schedule
Titles and Abstracts
Poster Titles
Participant ListMonday, December 9, 2019
Penn Pavilion, Duke UniversityTuesday, December 10, 2019
Penn Pavilion, Duke UniversityWednesday, December 11, 2019
Penn Pavilion, Duke UniversityDescription Speaker Slides Session 8: Unmeasured Confounders and Natural Experiments Difference-in-differences: more than meets the eye Laura Hatfeld, Harvard University A Bracketing Relationship between Difference-in-Differences and Lagged-Dependent-Variable Adjustment Peng Ding, University of California, Berkeley Testing Weak Nulls in Matched Observational Studies Colin Fogarty, MIT Bootstrapping Sensitivity Analysis for Inverse Probability Weighting Estimators Qingyuan Zhao, University of Cambridge Session 9: Causal Discovery Learning Hidden Causal Variables and Relations Kun Zhang, Carnegie Mellon University Simplicity Concepts for Causal Inference Peter Spirtes, Carnegie Mellon University Causal Discovery in Neuroimaging Data Frederick Eberhardt, Cal Tech Formal Working Groups Conclude Questions: email [email protected]