5 papers · 1 filter
Sequential Sensitivity Analysis for Multiple Assumptions: A Framework for Understanding Racial Disparity in Police Use of Force
Thomas Leavitt, Jake Bowers, Luke Miratrix
Inferring racial discrimination in police use of force -- the average causal effect of civilian race on use of force -- requires two assumptions about policing prior to potential u…
Variance estimation after matching or re-weighting
Xiang Meng, Aaron Smith, Luke Miratrix
This paper develops a variance estimation framework for matching estimators that enables valid population inference for treatment effects. We provide theoretical analysis of a vari…
Caliper Synthetic Matching: Generalized Radius Matching with Local Synthetic Controls
Jonathan Che, Xiang Meng, Luke Miratrix
Matching promises transparent causal inferences for observational data, making it an intuitive approach for many applications. In practice, however, standard matching methods often…
Empirical Bayes Double Shrinkage for Combining Biased and Unbiased Causal Estimates
Evan T. R. Rosenman, Francesca Dominici, Luke Miratrix
Motivated by the proliferation of observational datasets and the need to integrate non-randomized evidence with randomized controlled trials, causal inference researchers have rece…
Leveraging Population Outcomes to Improve the Generalization of Experimental Results
Melody Huang, Naoki Egami, Erin Hartman +1
Generalizing causal estimates in randomized experiments to a broader target population is essential for guiding decisions by policymakers and practitioners in the social and biomed…