On the causal structure of information bias and confounding bias in randomized trials

J Eval Clin Pract. 2009 Dec;15(6):1214-6. doi: 10.1111/j.1365-2753.2009.01347.x.


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'.

MeSH terms

  • Bias*
  • Causality
  • Confounding Factors, Epidemiologic*
  • Humans
  • Randomized Controlled Trials as Topic*
  • Research Design
  • Terminology as Topic