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Using directed acyclic graphs to determine whether multiple imputation or subsample-multiple imputation estimates of an exposure-outcome association are unbiased.

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Bibliographic Details
Title: Using directed acyclic graphs to determine whether multiple imputation or subsample-multiple imputation estimates of an exposure-outcome association are unbiased.
Authors: Madley-Dowd P; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; NIHR Biomedical Research Centre, University of Bristol, Bristol, United Kingdom.; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom., Hughes RA; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom., Mathur MB; Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, United States., Heron J; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom., Tilling K; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom.; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Source: American journal of epidemiology [Am J Epidemiol] 2026 Feb 05; Vol. 195 (2), pp. 505-514.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, N.I.H., Extramural
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 7910653 Publication Model: Print Cited Medium: Internet ISSN: 1476-6256 (Electronic) Linking ISSN: 00029262 NLM ISO Abbreviation: Am J Epidemiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1476-6256
DOI:10.1093/aje/kwaf265