39 citations · 65 across the 25 of their papers we have counts for
6 papers · 1 filter
Instrumental Variable Methods using Dynamic Interventions
Jacqueline A Mauro, Edward H Kennedy, Daniel Nagin
Recent work on dynamic interventions has greatly expanded the range of causal questions researchers can study while weakening identifying assumptions and yielding effects that are…
Visually Communicating and Teaching Intuition for Influence Functions
Aaron Fisher, Edward H. Kennedy
Estimators based on influence functions (IFs) have been shown to be effective in many settings, especially when combined with machine learning techniques. By focusing on estimating…
A nonparametric projection-based estimator for the probability of causation, with application to water sanitation in Kenya
Maria Cuellar, Edward H. Kennedy
Current estimation methods for the probability of causation (PC) make strong parametric assumptions or are inefficient. We derive a nonparametric influence-function-based estimator…
Causal effects based on distributional distances
Kwangho Kim, Jisu Kim, Edward H. Kennedy
Comparing counterfactual distributions can provide more nuanced and valuable measures for causal effects, going beyond typical summary statistics such as averages. In this work, we…
Efficient nonparametric causal inference with missing exposure information
Edward H. Kennedy
Missing exposure information is a very common feature of many observational studies. Here we study identifiability and efficient estimation of causal effects on vector outcomes, in…
Sharp instruments for classifying compliers and generalizing causal effects
Edward H. Kennedy, Sivaraman Balakrishnan, Max G'Sell
It is well-known that, without restricting treatment effect heterogeneity, instrumental variable (IV) methods only identify "local" effects among compliers, i.e., those subjects wh…