2 citations · 2 across the 4 of their papers we have counts for
6 papers
Minimax Rates for Learning Smooth Populations of Parameters
JungHo Lee, Edward H. Kennedy
We study pointwise estimation of a smooth binomial mixing density and characterize its minimax rates. Assuming that the mixing density is -Hölder smooth, we first consider the h…
Sensitivity analysis for incremental effects, with application to a study of victimization & offending
Shuying Shen, Valerio Bacak, Edward H. Kennedy
Sensitivity analysis for unmeasured confounding under incremental propensity score interventions remains relatively underdeveloped. Incremental interventions define stochastic trea…
Challenges in Statistics: A Dozen Challenges in Causality and Causal Inference
Carlos Cinelli, Avi Feller, Guido Imbens +3
Causality and causal inference have emerged as core research areas at the interface of modern statistics and domains including biomedical sciences, social sciences, computer scienc…
Learning Smooth Populations of Parameters with Trial Heterogeneity
JungHo Lee, Valerio Baćak, Edward H. Kennedy
We consider the classical problem of estimating the mixing distribution of binomial mixtures, but under trial heterogeneity and smoothness. This problem has been studied extensivel…
Incremental effects for continuous exposures
Kyle Schindl, Shuying Shen, Edward H. Kennedy
Causal inference problems often involve continuous treatments, such as dose, duration, or frequency. However, identifying and estimating standard dose-response estimands requires t…
Counterfactual Density Estimation using Kernel Stein Discrepancies
Diego Martinez-Taboada, Edward H. Kennedy
Causal effects are usually studied in terms of the means of counterfactual distributions, which may be insufficient in many scenarios. Given a class of densities known up to normal…