title: Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists.
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.
authors.affiliation: From the aDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; bSchool of Social and Community Medicine, University of Bristol, Bristol, United Kingdom; cDepartments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA; and dHarvard-MIT Division of Health Sciences and Technology, Boston, MA.
authors.forename: Mohammad Ali
authors.initials: MA
authors.lastname: Mansournia
authors.forename: Julian P T
authors.initials: JP
authors.lastname: Higgins
authors.forename: Jonathan A C
authors.initials: JA
authors.lastname: Sterne
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Hernán
mesh_terms: D015982:Bias; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D006801:Humans; D057194:Intention to Treat Analysis; D015588:Observer Variation; D010352:Patient Dropouts; D016032:Randomized Controlled Trials as Topic; D015983:Selection Bias