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Multiple imputation: review of theory, implementation and software
Harel O, Zhou XH.. Statistics in medicine, 2007-07-01
Topic: Risk, prevention and care in population studies
Missing data is a common complication in data analysis. In many medical settings missing data can cause difficulties in estimation, precision and inference. Multiple imputation (MI) (Multiple Imputation for Nonresponse in Surveys.
Key findings
- In many medical settings missing data can cause difficulties in estimation, precision and inference.
- Multiple imputation (MI) (Multiple Imputation for Nonresponse in Surveys.
- Wiley: New York, 1987) is a simulation-based approach to deal with incomplete data.
- Although there are many different methods to deal with incomplete data, MI has become one of the leading methods.
Why it matters
This paper reviews the theory, implementation and software for multiple imputation, a statistical method for handling missing data. It is a methods review with no bearing on treating, curing or preventing Alzheimer's disease.
Study details
- Evidence strengthLow
How this study scored 50/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Statistics in medicine) |
| Journal's citation record | 3 / 4 | Statistics in Medicine: journal h-index 309 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2007 — within 20 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 6 / 7 | Cited 430 times (OpenAlex, 2026-10-10) |
| Citations per year | 4 / 5 | 20.5 citations a year over 21 year(s) since 2007 |
| Impact for its field and year | 5 / 6 | Cited 20.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 2 / 4 | Cited 45 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Xiao‐Hua Zhou: h-index 65 (OpenAlex, whole career) |
| Institution's track record | 3 / 3 | University of Washington: institution h-index 3,540 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 17256804) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 50 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Harel, O., & Zhou, X. H. (2007). Multiple imputation: review of theory, implementation and software. Statistics in medicine. https://doi.org/10.1002/sim.2787
Vancouver
Harel O, Zhou XH. Multiple imputation: review of theory, implementation and software. Statistics in medicine. 2007. doi:10.1002/sim.2787. PMID: 17256804.
BibTeX
@article{harel2007-17256804,
author = {Harel, O. and Zhou, X. H.},
title = {{Multiple imputation: review of theory, implementation and software}},
journal = {Statistics in medicine},
year = {2007},
doi = {10.1002/sim.2787},
pmid = {17256804},
url = {https://doi.org/10.1002/sim.2787}
}
Later studies that cite this one
1 study in the alzhub library lists this one in its references.