American Journal of Epidemiology Advance Access originally published online on July 17, 2006
American Journal of Epidemiology 2006 164(4):312-314; doi:10.1093/aje/kwj238
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.
Invited Commentary |
Invited Commentary: Simple Models for a Complicated Reality
1 Epidemiology Branch, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD
2 Department of Epidemiology, Harvard School of Public Health, Boston, MA
3 Slone Epidemiology Center, Boston University, Boston, MA
Correspondence to Dr. Enrique F. Schisterman, Division of Epidemiology, Statistics and Prevention Research, NICHD, NIH, 6100 Executive Boulevard, 7B03, Rockville, MD 20852 (e-mail: schistee@mail.nih.gov).
Received for publication February 27, 2006. Accepted for publication March 6, 2006.
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INTRODUCTION |
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The renowned statistician George P. Box famously said that all models are wrong, but some are useful. Far from an indictment of statistical models, Box's statement can be taken to mean that even when complex realities are not exactly represented by simple fitted models, much can be learned. The paper by Basso et al. (1
) in this issue of the Journal provides an opportunity to consider the costs and benefits that arise from the simplification necessary for generating statistical models of complex biologic processes. Considering the relation among birth weight, mortality, and third factors, Basso et al. postulate that birth weight is not itself on the causal path to mortality; rather, the relation between birth weight and mortality might be explained by a confounding factor. The authors conclude that, to produce the observed inverse J shape of the birth-weight-specific mortality curve, the putative confounding factors (matrix X = (X1 |
ASSUMPTIONS |
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Gaussian distribution for birth weight
Uniform effect of risk factors
Noncausal effect of birth weight on neonatal mortality
4. Lack of interaction between factors X1 or X2 and birth weight
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CONCLUSIONS |
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Related articles in Am. J. Epidemiol.:
- Birth Weight and Mortality: Causality or Confounding?
- Olga Basso, Allen J. Wilcox, and Clarice R. Weinberg
Am. J. Epidemiol. 2006 164: 303-311.[Abstract] [FREE Full Text]
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O. Basso, A. J. Wilcox, and C. R. Weinberg Basso et al. Respond to "Simple Models for a Complicated Reality" Am. J. Epidemiol., August 15, 2006; 164(4): 315 - 316. [Full Text] [PDF]
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