The Annual Winter Workshop's theme this year is:
Recent Advances in Causal Inference and Mediation Analysis and their Applications
The workshop will focus on recent advances in causal inference and causal mediation analysis. Causal inference is essential for comparative effectiveness research and causal discoveries from (large) observational data (including EHRs). Causal mediation helps us understand how an exposure or intervention works through different pathways. Both become considerably more complex in the presence of interference, on networks, with time-varying exposures, and in big data settings with many potential confounders and/or many potential mediators. Important issues to be addressed include the complication of causal inference in the presence of interference, causal inference on networks, causal mediation analysis in the presence of many mediators, variable selection, sensitivity analysis for uncheckable assumptions (including unmeasured confounders) with applications to ‘omics, mental health, education, networks, and more.
Agenda
Guest speakers include:
1) Edo Airoldi, Harvard University
2) Jennifer Hill, New York University
3) Luke Keele, University of Pennsylvania
4) Fan Li, Duke University
5) Hongzhe Li, University of Pennsylvania (Biostat)
6) Jas Sekhon, University of California at Berkeley
7) Michael Sobel, Columbia University
8) Liz Stuart, Hopkins University
9) Eric Tchetgen, University of Pennsylvania (Wharton)
10) Stijn Vansteelandt, Ghent University (Belgium)
Conference Organizers: Dr. Michael Daniels and Dr. George Michailidis
Event Type
- Affiliate Award Fund Eligible
- NISS Sponsored
Host
Sponsor
Location
Policy
