Cited by 198Statistical Methods and Bayesian InferenceAdvanced Causal Inference TechniquesStatistical Methods in Clinical Trials

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Missing data: A statistical framework for practice

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Carpenter, James R., Smuk, Melanie·2021·Biometrical Journal

DOI 10.1002/bimj.202000196PMC PMC7615108

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Abstract

Missing data are ubiquitous in medical research, yet there is still uncertainty over when restricting to the complete records is likely to be acceptable, when more complex methods (e.g. maximum likelihood, multiple imputation and Bayesian methods) should be used, how they relate to each other and the role of sensitivity analysis. This article seeks to address both applied practitioners and researchers interested in a more formal explanation of some of the results. For practitioners, the framework, illustrative examples and code should equip them with a practical approach to address the issues raised by missing data (particularly using multiple imputation), alongside an overview of how the various approaches in the literature relate. In particular, we describe how multiple imputation can be readily used for sensitivity analyses, which are still infrequently performed. For those interested in more formal derivations, we give outline arguments for key results, use simple examples to show how methods relate, and references for full details. The ideas are illustrated with a cohort study, a multi‐centre case control study and a randomised clinical trial.

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Carpenter J. R., 2015, Handbook of missing data methodology, 23
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Authors: Carpenter, J. R., & Smuk, M.
Affiliations: London School of Hygiene & Tropical Medicine (GB)
Corresponding author: Carpenter, James R.
ORCID: Carpenter, James R.
Smuk, Melanie
Venue: Biometrical Journal
Publisher: Wiley
Published: 2021-02-24
Volume: 63
Issue: 5
Pages: 915-947
ISSN: 0323-3847 (ISSN-L)
1521-4036
DOI: 10.1002/bimj.202000196
PMC: PMC7615108
OpenAlex: W3130968222
Cited by: 198
References: 94
Citations by year: 2026: 38 · 2025: 54 · 2024: 36 · 2023: 32 · 2022: 31 · 2021: 7
FWCI: 4.92
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
creativecommons.org/licenses/by-nc/4.0/ (vor)
Locations: Biometrical Journal (publishedVersion, cc-by-nc)
PubMed (publishedVersion)
PubMed Central (acceptedVersion, cc-by-nc)
LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
Funders: Medical Research Council (MC_UU_12023/21, MC_UU_12023/29, MC_UU_00004/07)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords: missing data, multiple imputation, sensitivity analysis, maximum likelihood estimation, Bayesian analysis, missing data mechanisms, cohort studies, case-control study, randomized controlled trials
MeSH terms: Bayes Theorem, Data Interpretation, Statistical, Humans, Cohort Studies, Case-Control Studies, Uncertainty

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Missing data: A statistical framework for practice

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