Work

Causal Estimation with Functional Confounders.

Year: 2020

Type: article

Abstract: . Second, we develop conditions for nonparametric effect estimation based on the gradient fields of the functional confounder and the true outcome function. To estimate effects under these conditions, we develop Level-set Orthogonal Descent Estimation (LODE). Further, we prove error bounds on LODE's effect estimates, evaluate our methods on simulated and real data, and empirically demonstrate the value of EFC.

Source: PubMed

Authors: Aahlad Puli, Adler J Perotte, Rajesh Ranganath

Institutions: New York University, Columbia University

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funder: National Heart, Lung, and Blood Institute

Award: Deep probabilistic predictive models for stroke and coronary heart disease

OpenAlex ID: W3098550155

FWCI: 0.353

Cites: 13

Cited by: 2

Related to: 10