BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect

BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect

A method for estimating the conditional average treatment effect under the condition of censored time-to-event data, called BENK (the Beran Estimator with Neural Kernels), is proposed. The main idea behind the method is to apply the Beran estimator for estimating the survival functions of controls a...

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Bibliographic Details
Main Authors: Stanislav Kirpichenko, Lev Utkin, Andrei Konstantinov, Vladimir Muliukha
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Algorithms
Subjects:
treatment effect
survival analysis
Nadaraya–Watson regression
Beran estimator
neural network
meta-learner
Online Access:https://www.mdpi.com/1999-4893/17/1/40

Internet

https://www.mdpi.com/1999-4893/17/1/40

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