6 citations · 13 across the 6 of their papers we have counts for
6 papers · 1 filter
Network Interference in Micro-Randomized Trials
Shuangning Li, Stefan Wager
The micro-randomized trial (MRT) is an experimental design that can be used to develop optimal mobile health interventions. In MRTs, interventions in the form of notifications or m…
Doubly robust treatment effect estimation with missing attributes
Imke Mayer, Erik Sverdrup, Tobias Gauss +3
Missing attributes are ubiquitous in causal inference, as they are in most applied statistical work. In this paper, we consider various sets of assumptions under which causal infer…
Cross-Validation, Risk Estimation, and Model Selection
Stefan Wager
Cross-validation is a popular non-parametric method for evaluating the accuracy of a predictive rule. The usefulness of cross-validation depends on the task we want to employ it fo…
Covariate-Powered Empirical Bayes Estimation
Nikolaos Ignatiadis, Stefan Wager
We study methods for simultaneous analysis of many noisy experiments in the presence of rich covariate information. The goal of the analyst is to optimally estimate the true effect…
Learning When-to-Treat Policies
Xinkun Nie, Emma Brunskill, Stefan Wager
Many applied decision-making problems have a dynamic component: The policymaker needs not only to choose whom to treat, but also when to start which treatment. For example, a medic…
Estimating Treatment Effects with Causal Forests: An Application
Susan Athey, Stefan Wager
We apply causal forests to a dataset derived from the National Study of Learning Mindsets, and consider resulting practical and conceptual challenges. In particular, we discuss how…