A Regression-Based Approach to Robust Estimation and Inference for Genetic Covariance-Reference-Cited by-同舟云学术

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A Regression-Based Approach to Robust Estimation and Inference for Genetic Covariance

Published:2023-09-26 Issue: Volume: Page:1-13
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Wang Jianqiao¹,Li Sai²,Li Hongzhe³

Affiliation:

1. Department of Biostatistics, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA

2. Institute of Statistics and Data Science, Renmin University of China, Beijing, China

3. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA

Funder

NIH

Fundamental Research Funds for the Central Universities

Research Funds of Renmin University of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2023.2261669

Reference29 articles.

1. An atlas of genetic correlations across human diseases and traits

2. Semisupervised inference for explained variance in high dimensional linear regression and its applications

3. Celentano M. Montanari A. and Wei Y. (2020) “The Lasso with General Gaussian Designs with Applications to Hypothesis Testing ” arXiv preprint arXiv:2007.13716.

4. Double/debiased machine learning for treatment and structural parameters

5. Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

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