activity
20162021
most citedThe Generalized Oaxaca-Blinder Estimator

7 citations · 11 across the 4 of their papers we have counts for

collaborators

8 papers

stat.ME20211 cited

Randomization Inference for Composite Experiments with Spillovers and Peer Effects

Hui Xu, Guillaume Basse

Group-formation experiments, in which experimental units are randomly assigned to groups, are a powerful tool for studying peer effects in the social sciences. Existing design and…

math.ST20207 cited

The Generalized Oaxaca-Blinder Estimator

Kevin Guo, Guillaume Basse

After performing a randomized experiment, researchers often use ordinary-least squares (OLS) regression to adjust for baseline covariates when estimating the average treatment effe…

stat.ME20203 cited

A general theory of identification

Guillaume Basse, Iavor Bojinov

What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree on a definition in the context of parametric statistical models --- roughly, a p…

stat.ME2020

Combining Observational and Experimental Datasets Using Shrinkage Estimators

Evan Rosenman, Guillaume Basse, Art Owen +1

We consider the problem of combining data from observational and experimental sources to make causal conclusions. This problem is increasingly relevant, as the modern era has yield…

stat.ME2019

Minimax designs for causal effects in temporal experiments with treatment habituation

Guillaume Basse, Yi Ding, Panos Toulis

Randomized experiments are the gold standard for estimating the causal effects of an intervention. In the simplest setting, each experimental unit is randomly assigned to receive t…

stat.ME2017

Limitations of design-based causal inference and A/B testing under arbitrary and network interference

Guillaume Basse, Edoardo Airoldi

Randomized experiments on a network often involve interference between connected units; i.e., a situation in which an individual's treatment can affect the response of another indi…