From the 1 of 7 linked papers with an AI index.
7 papers
On regression with estimated covariates and conditional effects given the propensity score
Jiaqi Wu, Matteo Bonvini, Edward H. Kennedy +2
The paper studies how to estimate a nonparametric regression when some covariates are themselves estimated, proposing debiased influence‑function and bias‑corrected plug‑in methods…
Fast convergence rates for dose-response estimation
Matteo Bonvini, Edward H. Kennedy
We consider the problem of estimating a dose-response curve. Continuous treatments arise often in practice, e.g. in the form of time spent on an operation, distance traveled to a l…
Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding
Ashesh Rambachan, Amanda Coston, Edward Kennedy
Predictive algorithms inform consequential decisions in settings with selective labels: outcomes are observed only for units selected by past decision makers. This creates an ident…
Semiparametric sensitivity analysis: unmeasured confounding in observational studies
Razieh Nabi, Matteo Bonvini, Edward H. Kennedy +3
Establishing cause-effect relationships from observational data often relies on untestable assumptions. It is crucial to know whether, and to what extent, the conclusions drawn fro…
The Fundamental Limits of Structure-Agnostic Functional Estimation
Sivaraman Balakrishnan, Edward H. Kennedy, Larry Wasserman
Many recent developments in causal inference, and functional estimation problems more generally, have been motivated by the fact that classical one-step (first-order) debiasing met…
Efficient Generalization and Transportation
Zhenghao Zeng, Edward H. Kennedy, Lisa M. Bodnar +1
When estimating causal effects, it is important to assess external validity, i.e., determine how useful a given study is to inform a practical question for a specific target popula…