EBMH NOTEBOOK
Understanding confounding and mediation
Correspondence to:
Dr Michael A Babyak, Duke University Medical Center, Box 3119 DUMC, Durham, NC 27710, USA; michael.babyak@duke.edu
| The first 150 words of the full text of this article appear below. |
In both experimental and observational studies, many researchers attempt, often implicitly, to identify causal relations among variables. In trying to understand the possible causal processes that might have generated their data, the concepts of confounding and mediation play a prominent role. The two phenomena are often confused, and indeed are not always readily distinguishable. In the present paper, I will present a brief, somewhat simplified, introduction to confounding and mediation. I will present basic defining criteria, how to distinguish the two and also the problem of cases in which the distinction is not clear, along with some final caveats.
The term confound arises from the Latin confundere, to pour together or mix.1 The English word confuse arises from the same Latin root (http://www.merriam-webster.com/). In the context of empirical research, the term confounding is most often encountered in situations where some "predictor" of interest, let’s call it a
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