260 citations · 828 across the 46 of their papers we have counts for
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Random Graph Asymptotics for Treatment Effect Estimation under Network Interference
Shuangning Li, Stefan Wager
The network interference model for causal inference places all experimental units at the vertices of an undirected exposure graph, such that treatment assigned to one unit may affe…
Noise-Induced Randomization in Regression Discontinuity Designs
Dean Eckles, Nikolaos Ignatiadis, Stefan Wager +1
Regression discontinuity designs assess causal effects in settings where treatment is determined by whether an observed running variable crosses a pre-specified threshold. Here we…
Estimating heterogeneous treatment effects with right-censored data via causal survival forests
Yifan Cui, Michael R. Kosorok, Erik Sverdrup +2
Forest-based methods have recently gained in popularity for non-parametric treatment effect estimation. Building on this line of work, we introduce causal survival forests, which c…