Unveiling the Unobservable: Causal Inference on Multiple Derived Outcomes-Reference-Cited by-同舟云学术

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Unveiling the Unobservable: Causal Inference on Multiple Derived Outcomes

Published:2023-08-31 Issue: Volume: Page:1-12
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Qiu Yumou¹^ORCID,Sun Jiarui²,Zhou Xiao-Hua³^ORCID

Affiliation:

1. School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing, China

2. School of Mathematical Sciences, Peking University, Beijing, China

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

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Novo Nordisk A/S

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2023.2252135

Reference35 articles.

1. Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

2. Disruption of Large-Scale Brain Systems in Advanced Aging

3. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies

4. Doubly Robust Estimation in Missing Data and Causal Inference Models

5. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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1. Patterns identification using blind source separation with application to neural activities associated with anticipated falls;Information Sciences;2025-01

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