activity
20132024
most citedEstimating Average Causal Effects Under General Interference, with Application to a Social Network Experiment

257 citations · 344 across the 21 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

stat.ME2021

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…

stat.ME2021★ 9 cited

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…

stat.ME2021★ 4 cited

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…

stat.ME2021★ 2 cited

Dyadic Clustering in International Relations

Jacob Carlson, Trevor Incerti, P. M. Aronow

Quantitative empirical inquiry in international relations often relies on dyadic data. Standard analytic techniques do not account for the fact that dyads are not generally indepen…

stat.ME2021

Inference in Spatial Experiments with Interference using the SpatialEffect Package

Cyrus Samii, Ye Wang, Jonathan Sullivan +1

This paper presents methods for analyzing spatial experiments when complex spillovers, displacement effects, and other types of "interference" are present. We present a robust, des…