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American Journal of Epidemiology Advance Access originally published online on July 5, 2007
American Journal of Epidemiology 2007 166(6):659-661; doi:10.1093/aje/kwm174
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American Journal of Epidemiology © The Author 2007. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Response to Invited Commentary

Fewell et al. Respond to "Fuel for Debate"

Zoe Fewell, George Davey Smith and Jonathan A. C. Sterne

From the Department of Social Medicine, University of Bristol, Bristol, United Kingdom

Correspondence to Prof. Jonathan A. C. Sterne, Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol BS8 2PR, United Kingdom (e-mail: Jonathan.Sterne@bristol.ac.uk).

Received for publication December 13, 2006. Accepted for publication May 3, 2007.

The first 10% of the full text of this article appears below.

In our paper (1), we considered the extent and patterns of bias in estimates of exposure-outcome associations that can result from residual or unmeasured confounding, when there is no true association between the exposure and the outcome. We conducted simulations with two or four confounders. When the confounders are uncorrelated, bias in the exposure effect estimate increases as the amount of residual and unmeasured confounding increases. However, patterns are more complex for correlated confounders: It is possible for the bias to increase when confounder measurement error decreases or when additional confounders are controlled for.

In his commentary, Dr. James Marshall (2) correctly identifies some limitations of our . . . [Full Text of this Article]


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Related articles in Am. J. Epidemiol.:

The Impact of Residual and Unmeasured Confounding in Epidemiologic Studies: A Simulation Study
Zoe Fewell, George Davey Smith, and Jonathan A. C. Sterne
Am. J. Epidemiol. 2007 166: 646-655. [Abstract] [FREE Full Text]