Cited by 285Advanced Causal Inference TechniquesMeta-analysis and systematic reviewsStatistical Methods in Clinical Trials

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Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists

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Mansournia, Mohammad Ali, Higgins, Julian P. T., Sterne, Jonathan A. C., Hernán, Miguel A.·2017·Epidemiology

DOI 10.1097/ede.0000000000000564PMC PMC5130591

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Abstract

Trialists and epidemiologists often employ different terminology to refer to biases in randomized trials and observational studies, even though many biases have a similar structure in both types of study. We use causal diagrams to represent the structure of biases, as described by Cochrane for randomized trials, and provide a translation to the usual epidemiologic terms of confounding, selection bias, and measurement bias. This structural approach clarifies that an explicit description of the inferential goal-the intention-to-treat effect or the per-protocol effect-is necessary to assess risk of bias in the estimates. Being aware of each other's terminologies will enhance communication between trialists and epidemiologists when considering key concepts and methods for causal inference.

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Self-citation

Authors: Mansournia, M. A., Higgins, J. P. T., Sterne, J. A. C., & Hernán, M. A.
Affiliations: Harvard University (US)
ORCID: Higgins, Julian P. T.
Sterne, Jonathan A. C.
Venue: Epidemiology
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2017-01
Volume: 28
Issue: 1
Pages: 54-59
ISSN: 1044-3983 (ISSN-L)
DOI: 10.1097/ede.0000000000000564
PMC: PMC5130591
OpenAlex: W2336975416
Cited by: 285
References: 25
Citations by year: 2026: 18 · 2025: 30 · 2024: 30 · 2023: 29 · 2022: 40 · 2021: 39 · 2020: 42 · 2019: 29 · 2018: 17 · 2017: 9
FWCI: 19.21
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Epidemiology (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Bristol Research (University of Bristol) (acceptedVersion, other-oa)
Explore Bristol Research (submittedVersion, other-oa)
Funders: National Institute for Health and Care Research (NF-SI-0611-10168, NF-SI-0616-10111)
Medical Research Council (MR/M025209/1, MR/K025643/1)
National Cancer Institute (P01CA134294, R35CA197449)
National Institute of Allergy and Infectious Diseases (R01AI102634)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords: confounding, selection bias, measurement bias, causal graphs, intention-to-treat effect, risk of bias, terminology translation, causal inference
MeSH terms: Humans, Patient Dropouts, Observer Variation, Bias, Selection Bias, Causality, Confounding Factors, Epidemiologic, Randomized Controlled Trials as Topic, Intention to Treat Analysis

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Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists

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