Tu, Y-K., Gunnell, D. and Gilthorpe, M.S. (2008) Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox. Emerging Themes in Epidemiology, 5 (2). ISSN 1742-7622Full text available as:
Available under licence : See the attached licence file.
This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results.
|Copyright, Publisher and Additional Information:||© 2008 Tu et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License. (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.|
|Institution:||The University of Leeds|
|Academic Units:||The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Dentistry (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Division of Epidemiology & Biostatistics (Leeds)
|Depositing User:||Sherpa Assistant|
|Date Deposited:||17 Oct 2008 12:46|
|Last Modified:||08 Feb 2013 17:05|
|Publisher:||BioMed Central Ltd|