Missing data: A statistical framework for practice.
complete records
missing data
multiple imputation
sensitivity analysis
Journal
Biometrical journal. Biometrische Zeitschrift
ISSN: 1521-4036
Titre abrégé: Biom J
Pays: Germany
ID NLM: 7708048
Informations de publication
Date de publication:
06 2021
06 2021
Historique:
revised:
19
11
2020
received:
23
06
2020
accepted:
24
11
2020
pubmed:
25
2
2021
medline:
16
10
2021
entrez:
24
2
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33624862
doi: 10.1002/bimj.202000196
pmc: PMC7615108
mid: EMS177343
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
915-947Subventions
Organisme : Medical Research Council
ID : MC_UU_00004/07
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_12023/21
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_12023/29
Pays : United Kingdom
Informations de copyright
© 2021 The Authors. Biometrical Journal published by Wiley-VCH GmbH.
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