Journal
EPIDEMIOLOGY
Volume 28, Issue 1, Pages 54-59Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/EDE.0000000000000564
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Funding
- NIH [R01 AI102634]
- Methods Innovation Fund grant from the Cochrane Collaboration
- National Institute for Health Research [NF-SI-0611-10168]
- MRC [MR/M025209/1, MR/K025643/1] Funding Source: UKRI
- NATIONAL CANCER INSTITUTE [P01CA134294] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R01AI102634] Funding Source: NIH RePORTER
- Medical Research Council [MR/M025209/1, MR/K025643/1] Funding Source: researchfish
- National Institute for Health Research [NF-SI-0616-10111] Funding Source: researchfish
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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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