A Meta-Learning Approach for Estimating Heterogeneous Treatment Effects Under Hölder Continuity
Estimating heterogeneous treatment effects plays a vital role in many statistical applications, such as precision medicine and precision marketing. In this paper, we propose a novel meta-learner, termed RXlearner for estimating the conditional average treatment effect (CATE) within the general frame...
Saved in:
| Main Authors: | Zhihao Zhao, Congyang Zhou |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/11/1739 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Copula-Driven CNN-LSTM Framework for Estimating Heterogeneous Treatment Effects in Multivariate Outcomes
by: Jong-Min Kim
Published: (2025-07-01) -
Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy’s impact on ART adherence
by: Abraham Keffale Mengistu, et al.
Published: (2025-08-01) -
Treatment effects of Xuebijing injection in patients with sepsis by clinical phenotype: a post hoc analysis of the EXIT-SEP trialResearch in context
by: Xiran Lou, et al.
Published: (2025-08-01) -
Heterogeneity of Cardiovascular Effects of Second‐Line Glucose‐Lowering Therapies in Adults With Type 2 Diabetes Across the Range of Moderate Baseline Cardiovascular Risk
by: Yihong Deng, et al.
Published: (2025-08-01) -
On the Formation of Professionally Specialized Competencies and Training of Specialists and Managers in the Pharmacovigilance System of the Marketing Authorization Holder
by: E. Yu. Kurganova, et al.
Published: (2022-12-01)