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Journal of the American Statistical Association Volume 116, 2021 - Issue 534
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Theory and Methods Special Issue on Precision Medicine and Individualized Policy Discovery, Part II

Discussion of Kallus (2020) and Mo, Qi, and Liu (2020): New Objectives for Policy Learning

Sijia Lia Department of Biostatistics, University of Washington, Seattle, WA; View further author information
,
Xiudi Lia Department of Biostatistics, University of Washington, Seattle, WA; View further author information
&
Alex Luedtkeb Department of Statistics, University of Washington, Seattle, WACorrespondence[email protected]
View further author information
Pages 680-689 | Received 14 Sep 2020, Accepted 03 Oct 2020, Published online: 01 Apr 2021
 
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This article refers to:
More Efficient Policy Learning via Optimal Retargeting
Learning Optimal Distributionally Robust Individualized Treatment Rules
This article is related to:
Introduction to the Theory and Methods Special Issue on Precision Medicine and Individualized Policy Discovery
View responses to this article:
Rejoinder: New Objectives for Policy Learning
Rejoinder: New Objectives for Policy Learning

Additional information

Funding

This work was supported by the National Institutes of Health (NIH) under award number DP2-LM013340. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
This article is part of the following collections:
Theory and Methods Special Issue on Precision Medicine and Individualized Policy Discovery

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