Cited by 538Statistical Methods and Bayesian InferenceStatistical Methods in EpidemiologyAdvanced Causal Inference Techniques

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Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis

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Groenwold, Rolf H.H., White, Ian R., Donders, A. Rogier T., Carpenter, James R., Altman, Douglas G., Moons, Karel G.M.·2012·Canadian Medical Association Journal

DOI 10.1503/cmaj.110977PMC PMC3414599

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Abstract

Missing data are a frequently encountered problem in epidemiologic and clinical research.[1][1],[2][2] One approach is to include in the analysis only those participants without missing observations (complete or available case analysis).[1][1]–[4][3] However, in addition to reducing statistical

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Review: a gentle introduction to imputation of missing values.
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Method
Using the outcome for imputation of missing predictor values was preferred
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Authors: Groenwold, R. H. H., White, I. R., Donders, A. R. T., Carpenter, J. R., Altman, D. G., & Moons, K. G. M.
Affiliations: University Medical Center Utrecht (NL)
ORCID: Groenwold, Rolf H.H.
White, Ian R.
Donders, A. Rogier T.
Carpenter, James R.
Altman, Douglas G.
Moons, Karel G.M.
Venue: Canadian Medical Association Journal
Publisher: CMA Impact Inc.
Published: 2012-02-27
Volume: 184
Issue: 11
Pages: 1265-1269
ISSN: 0820-3946 (ISSN-L)
1488-2329
DOI: 10.1503/cmaj.110977
PMC: PMC3414599
OpenAlex: W2122717603
Cited by: 538
References: 21
Citations by year: 2026: 69 · 2025: 91 · 2024: 90 · 2023: 59 · 2022: 65 · 2021: 48 · 2020: 40 · 2019: 23 · 2018: 17 · 2017: 14 · 2016: 9 · 2015: 4 · 2014: 3 · 2013: 5
FWCI: 3.66
Type: journal article
Language: en
Open access: gold
doi.org
Locations: Canadian Medical Association Journal (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Radboud Repository (Radboud University) (submittedVersion)
Funders: Cancer Research UK (C5529)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (917-46-360)
Economic and Social Research Council (ES/G026300/1)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords: missing data, complete case analysis, multiple imputation, missing data mechanisms, clinical research
MeSH terms: Humans, Research Design, Statistics as Topic, Bias, Biomedical Research

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Missing covariate data in clinical research: when and when not to use the missing-indicator method for analysis

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