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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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BackgroundMethodInfluentialSelf-citationMultiple Imputation of Missing Values: Update
Royston, P. (2005) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x0500500204 · Cited by 1,683
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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
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