Sensitivity analysis after multiple imputation under missing…
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- DOI 10.1177/0962280206075303
- PMID https://pubmed.ncbi.nlm.nih.gov/17621471
- OpenAlex ID W2085438886
- Type Article
- Language EN
- Published 01 Jun 2007
- Volume 16 (3)
- Pages 259–275
- Source Statistical Methods in Medical Research
- Publisher SAGE Publishing
- FWCI 8.52
- Countries 1
- Institutions 2
- Added 24 Jun 2016
- Updated 16 Oct 2026
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Sensitivity analysis after multiple imputation under missing at random: a weighting approach
Article 2007 EN
Multiple imputation (MI) is now well established as a flexible, general, method for the analysis of data sets with missing values. Most implementations assume the missing data are ;missing at random' (MAR), that is, given the observed data, the reason for the missing data does not depend on the unseen data. However, although this is a helpful and simplifying working assumption, it is unlikely to b…
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3 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | James R. Carpenter Corresponding | London School of Hygiene & Tro… (GB) | |
| 2 | Michael G. Kenward | London School of Hygiene & Tro… (GB) | |
| 3 | Ian R. White | MRC Biostatistics Unit (GB) |
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