Journal
JOURNAL OF EVALUATION IN CLINICAL PRACTICE
Volume 15, Issue 6, Pages 1214-1216Publisher
WILEY
DOI: 10.1111/j.1365-2753.2009.01347.x
Keywords
causal diagrams; confounding; directed acyclic graphs; information bias; measurement bias; randomized trials
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Randomized trials are undoubtedly different from observational studies, but authors sometimes propose differences between these designs that do not exist. In this article we examine two claims about randomized trials: first, a recent claim that the causal structure of exposure measurement (information) bias in a randomized trial differs from the causal structure of that bias in an observational study. Second, a long-standing claim that confounding bias cannot operate in a randomized trial - if randomization was perfectly implemented. Using causal diagrams (causal directed acyclic graphs), we show that both claims are false in the context of an intention-to-treat analysis. We also describe a previously unrecognized mechanism of information bias, and suggest that the term 'information bias' should replace the terms 'measurement bias' and 'observation bias'.
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