2 citations · 7 across the 8 of their papers we have counts for
16 papers
Sensitivity Analysis for Marginal Structural Models
Matteo Bonvini, Edward Kennedy, Valerie Ventura +1
We introduce several methods for assessing sensitivity to unmeasured confounding in marginal structural models; importantly we allow treatments to be discrete or continuous, static…
Incremental causal effects: an introduction and review
Matteo Bonvini, Alec McClean, Zach Branson +1
In this chapter, we review the class of causal effects based on incremental propensity scores interventions proposed by Kennedy [2019]. The aim of incremental propensity score inte…
FADE: FAir Double Ensemble Learning for Observable and Counterfactual Outcomes
Alan Mishler, Edward Kennedy
Methods for building fair predictors often involve tradeoffs between fairness and accuracy and between different fairness criteria, but the nature of these tradeoffs varies. Recent…
Doubly robust capture-recapture methods for estimating population size
Manjari Das, Edward H. Kennedy, Nicholas P. Jewell
Estimation of population size using incomplete lists (also called the capture-recapture problem) has a long history across many biological and social sciences. For example, human r…
Comment on "Statistical Modeling: The Two Cultures" by Leo Breiman
Matteo Bonvini, Alan Mishler, Edward H. Kennedy
Motivated by Breiman's rousing 2001 paper on the "two cultures" in statistics, we consider the role that different modeling approaches play in causal inference. We discuss the rela…
Semiparametric counterfactual density estimation
Edward H. Kennedy, Sivaraman Balakrishnan, Larry Wasserman
Causal effects are often characterized with averages, which can give an incomplete picture of the underlying counterfactual distributions. Here we consider estimating the entire co…