1 citations · 1 across the 4 of their papers we have counts for
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Integer Programming for Generalized Causal Bootstrap Designs
Jennifer Brennan, Sébastien Lahaie, Adel Javanmard +2
In experimental causal inference, we distinguish between two sources of uncertainty: design uncertainty, due to the treatment assignment mechanism, and sampling uncertainty, when t…
Supergeo Design: Generalized Matching for Geographic Experiments
Aiyou Chen, Nick Doudchenko, Shunhua Jiang +2
We propose a generalization of the standard matched pairs design in which experimental units (often geographic regions or geos) may be combined into larger units/regions called "su…
Causal inference with bipartite designs: A generalized propensity score approach
Nick Doudchenko, Minzhengxiong Zhang, Evgeni Drynkin +5
Bipartite experiments, in which one set of units receives a treatment while outcomes are measured on another set, have recently garnered attention for their ability to capture inte…