Identifying Effects of Multiple Treatments in the Presence of Unmeasured Confounding-Reference-Cited by-同舟云学术

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Identifying Effects of Multiple Treatments in the Presence of Unmeasured Confounding

Published:2022-02-28 Issue: Volume: Page:1-15
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Miao Wang¹^ORCID,Hu Wenjie¹,Ogburn Elizabeth L.²^ORCID,Zhou Xiao-Hua³

Affiliation:

1. Department of Probability and Statistics, Peking University, Beijing, PR China

2. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

3. Department of Biostatistics and Beijing International Center for Mathematical Research, Peking University, Beijing, PR China

Funder

Beijing Natural Science Foundation

National Natural Science Foundation of China

ONR

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2021.2023551

Reference74 articles.

1. Singular value decomposition for genome-wide expression data processing and modeling

2. Examples of L2-complete and boundedly-complete distributions

3. Identification of Causal Effects Using Instrumental Variables

4. Comment on: “The Blessings of Multiple Causes” by Yixin Wang and David M. Blei

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