Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification-Reference-Cited by-同舟云学术

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Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Published:2022-09-21 Issue:28 Volume:41 Page:5501-5516
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Beesley Lauren J.¹²^ORCID,Mukherjee Bhramar¹^ORCID

Affiliation:

1. Department of Biostatistics University of Michigan Michigan USA

2. Information Systems and Modeling Los Alamos National Laboratory New Mexico USA

Funder

Comprehensive Cancer Center, University of Michigan

Division of Mathematical Sciences

Laboratory Directed Research and Development

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9579

Reference13 articles.

1. A General Framework for Considering Selection Bias in EHR-Based Studies: What Data are Observed and Why?

2. PIE: A prior knowledge guided integrated likelihood estimation method for bias reduction in association studies using electronic health records data

3. Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records

4. A simple model for potential use with a misclassified binary outcome in epidemiology

5. Statistical inference for association studies using electronic health records: handling both selection bias and outcome misclassification

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Systematic data quality assessment of electronic health record data to evaluate study-specific fitness: Report from the PRESERVE research study;PLOS Digital Health;2024-06-27

2. To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice;Journal of the American Medical Informatics Association;2024-05-14

3. A framework for understanding selection bias in real-world healthcare data;Journal of the Royal Statistical Society Series A: Statistics in Society;2024-05-02

4. Canadian COVID-19 host genetics cohort replicates known severity associations;PLOS Genetics;2024-03-22

5. To weight or not to weight? Studying the effect of selection bias in three large EHR-linked biobanks;2024-02-13

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