Statistics Annual Winter Workshop 2019

January 18 - 19, 2019

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.


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


University of Florida, Department of Statistics


University of Florida Informatics Institute
University of Florida, Department of Statistics
National Institute of Statistics Sciences


J. Wayne Reitz Union
655 Reitz Union Drive
United States
Statistics Winter Workshop 2019
University of Florida, Informatics Institute