Hey! We’re throwing a conference:
Varying Treatment Effects
The literature on causal inference focuses on estimating average effects, but the very notion of an “average effect” acknowledges variation. Relevant buzzwords are treatment interactions, situational effects, and personalized medicine. In this one-day conference we shall focus on varying effects in social science and policy research, with particular emphasis on Bayesian modeling and computation.
The focus will be on applied problems in social science.
The organizers are Jim Savage, Jennifer Hill, Beth Tipton, Rachael Meager, Andrew Gelman, Michael Sobel, and Jose Zubizarreta.
And here’s the schedule:
1. Heterogeneity across studies in meta-analyses of impact evaluations.
– Michael Kremer, Harvard
– Greg Fischer, LSE
– Rachael Meager, MIT
– Beth Tipton, Columbia
10-45 – 11 coffee break
2. Heterogeneity across sites in multi-site trials.
– David Yeager, UT Austin
– Avi Feller, Berkeley
– Luke Miratrix, Harvard
– Ben Goodrich, Columbia
– Michael Weiss, MDRC
3. Heterogeneity in experiments versus quasi-experiments.
– Vivian Wong, University of Virginia
– Michael Gechter, Penn State
– Peter Steiner, U Wisconsin
– Bryan Keller, Columbia
3:00 – 3:30 afternoon break
4. Heterogeneous effects at the structural/atomic level.
– Jennifer Hill, NYU
– Peter Rossi, UCLA
– Shoshana Vasserman, Harvard
– Jim Savage, Lendable Inc.
– Uri Shalit, NYU
Closing remarks: Andrew Gelman
Please register for the conference here. Admission is free but we would prefer if you register so we have a sense of how many people will show up.
We’re expecting lots of lively discussion.
P.S. Signup for outsiders seems to have filled up. Columbia University affiliates who are interested in attending should contact me directly.