257 citations · 344 across the 21 of their papers we have counts for
22 papers
Randomization-based confidence sets for the local average treatment effect
P. M. Aronow, Haoge Chang, Patrick Lopatto
We consider the problem of generating confidence sets in randomized experiments with noncompliance. We show that a refinement of a randomization-based procedure proposed by Imbens…
Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry
Serena Wang, Stephen Bates, P. M. Aronow +1
From the social sciences to machine learning, it has been well documented that metrics to be optimized are not always aligned with social welfare. In healthcare, Dranove et al. (20…
Fast computation of exact confidence intervals for randomized experiments with binary outcomes
P. M. Aronow, Haoge Chang, Patrick Lopatto
Given a randomized experiment with binary outcomes, exact confidence intervals for the average causal effect of the treatment can be computed through a series of permutation tests.…
Exact Bias Correction for Linear Adjustment of Randomized Controlled Trials
Haoge Chang, Joel Middleton, P. M. Aronow
In an influential critique of empirical practice, Freedman (2008) showed that the linear regression estimator was biased for the analysis of randomized controlled trials under the…
Nonparametric identification is not enough, but randomized controlled trials are
P. M. Aronow, James M. Robins, Theo Saarinen +2
We argue that randomized controlled trials (RCTs) are special even among settings where average treatment effects are identified by a nonparametric unconfoundedness assumption. Thi…
On the reliability of published findings using the regression discontinuity design in political science
Drew Stommes, P. M. Aronow, Fredrik Sävje
The regression discontinuity (RD) design offers identification of causal effects under weak assumptions, earning it a position as a standard method in modern political science rese…