26 citations · 72 across the 16 of their papers we have counts for
17 papers
Population Interference in Panel Experiments
Kevin Han, Iavor Bojinov, Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in s…
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…
Conditional As-If Analyses in Randomized Experiments
Nicole E. Pashley, Guillaume W. Basse, Luke W. Miratrix
The injunction to `analyze the way you randomize' is well-known to statisticians since Fisher advocated for randomization as the basis of inference. Yet even those convinced by the…
A Causal Framework for Observational Studies of Discrimination
Johann Gaebler, William Cai, Guillaume Basse +3
In studies of discrimination, researchers often seek to estimate a causal effect of race or gender on outcomes. For example, in the criminal justice context, one might ask whether…
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…
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…
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…
A Graph-Theoretic Approach to Randomization Tests of Causal Effects Under General Interference
David Puelz, Guillaume Basse, Avi Feller +1
Interference exists when a unit's outcome depends on another unit's treatment assignment. For example, intensive policing on one street could have a spillover effect on neighboring…
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…
Randomization tests for peer effects in group formation experiments
Guillaume Basse, Peng Ding, Avi Feller +1
Measuring the effect of peers on individuals' outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and unobservable…
Conditional randomization tests of causal effects with interference between units
Guillaume Basse, Avi Feller, Panos Toulis
Many causal questions involve interactions between units, also known as interference, for example between individuals in households, students in schools, or firms in markets. In th…
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…
Analyzing two-stage experiments in the presence of interference
Guillaume Basse, Avi Feller
Two-stage randomization is a powerful design for estimating treatment effects in the presence of interference; that is, when one individual's treatment assignment affects another i…
Parallel Markov Chain Monte Carlo via Spectral Clustering
Guillaume W. Basse, Natesh S. Pillai, Aaron Smith
As it has become common to use many computer cores in routine applications, finding good ways to parallelize popular algorithms has become increasingly important. In this paper, we…
Randomization and The Pernicious Effects of Limited Budgets on Auction Experiments
Guillaume W. Basse, Hossein Azari Soufiani, Diane Lambert
Buyers (e.g., advertisers) often have limited financial and processing resources, and so their participation in auctions is throttled. Changes to auctions may affect bids or thrott…
Observational studies with unknown time of treatment
Guillaume W. Basse, Alexander Volfovsky, Edoardo M. Airoldi
Time plays a fundamental role in causal analyses, where the goal is to quantify the effect of a specific treatment on future outcomes. In a randomized experiment, times of treatmen…
Model-assisted design of experiments in the presence of network correlated outcomes
Guillaume W. Basse, Edoardo M. Airoldi
We consider the problem of how to assign treatment in a randomized experiment, in which the correlation among the outcomes is informed by a network available pre-intervention. Work…