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Multiple Imputation by Chained Equations (MICE): Implementation in Stata
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Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors studies in medicine, multiple imputation is becoming the standard route to estimating models with missing covariate data under a missing-at-random assumption. We describe ice, an implementation in Stata of the MICE approach to multiple imputation. Real data from an observational study in ovarian cancer are used to illustrate the most important of the many options available with ice. We remark briefly on the new database architecture and procedures for multiple imputation introduced in releases 11 and 12 of Stata.
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“We used multiple imputation to deal with potential missing data biases, imputing 20 complete data sets using chained equations [50].”
From Electronic media use and academic performance in late childhood: A longitudinal study (2020) · cites this paper as [50]
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Metadata
- Authors
- Royston, P., & White, I.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2011
- Volume
- 45
- Issue
- 4
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1781481323
- Cited by
- 1,248
- References
- 22
- Citations by year
- 2026: 56 · 2025: 99 · 2024: 95 · 2023: 124 · 2022: 134 · 2021: 159 · 2020: 119 · 2019: 107 · 2018: 97 · 2017: 76 · 2016: 62 · 2015: 46 · 2014: 44 · 2013: 24 · 2012: 3
- FWCI
- 20.49
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Journal of Statistical Software (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Data Analysis with R
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- multiple imputation, chained equations, mice, missing data, missing at random, Stata, ovarian cancer, database architecture
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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