4 years ago

Hidden Biases in Observational Epidemiology: The Case of Unmeasured Confounding

Cande V. Ananth, Enrique F. Schisterman
Observational studies, when done well, enables inferences of causal associations. However, most observational studies cannot achieve inferences regarding causality, because of the limitations of the design itself and the strong potential for biases, particularly unmeasured confounding bias. An unmeasured confounder, by definition, is a variable that is related to both the exposure and the outcome that might account for the apparent observed association. This article is protected by copyright. All rights reserved.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1111/1471-0528.14960

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