A multiple imputation‐based sensitivity analysis approach fo…
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- DOI 10.1002/sim.9723
- PMID https://pubmed.ncbi.nlm.nih.gov/36997162
- PMCID https://www.ncbi.nlm.nih.gov/pmc/articles/10718304
- OpenAlex ID W4361246190
- Type Article
- Language EN
- Published 30 Mar 2023
- Volume 42 (14)
- Pages 2275–2292
- Source Statistics in Medicine
- Publisher Wiley
- FWCI 0.82
- Countries 1
- Institutions 3
- Added 31 Mar 2023
- Updated 29 Oct 2026
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A multiple imputation‐based sensitivity analysis approach for regression analysis with a missing not at random covariate
Article 2023 EN Green
Missing covariate problems are common in biomedical and electrical medical record data studies while evaluating the relationship between a biomarker and certain clinical outcome, when biomarker data are not collected for all subjects. However, missingness mechanism is unverifiable based on observed data. If there is a suspicion of missing not at random (MNAR), researchers often perform sensitivity…
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1 SDGsAuthors & Affiliations
4 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Chiu‐Hsieh Hsu Corresponding | University of Arizona (US) | |
| 2 | Yulei He | Centers for Disease Control an… (US) National Center for Health Sta… (US) | |
| 3 | Chengcheng Hu | University of Arizona (US) | |
| 4 | Wei Zhou | University of Arizona (US) |
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