• Eyal Shahar and Doron J Shahar.
• Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson,AZ 85724, USA. shahar@email.arizona.edu
• J Eval Clin Pract. 2009 Dec 1; 15 (6): 1214-6.

AbstractRandomized 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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