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American Journal of Epidemiology Vol. 149, No. 12: 1077-1086
Copyright © 1999 by The Johns Hopkins University School of Hygiene and Public Health


article-commentary

Presenting Statistical Uncertainty in Trends and Dose-Response Relations

Sander Greenland1, Karin B. Michels2,3, James M. Robins3,4, Charles Poole5 and Walter C. Willett2,3,6

1Department of Epidemiology, UCLA School of Public Health Los Angeles, CA
2Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School Boston, MA
3Department of Epidemiology, Harvard School of Public Health Boston, MA
4Department of Biostatistics, Harvard School of Public Health Boston, MA
5Department of Epidemiology, University of North Carolina School of Public Health Chapel Hill, NC
6Department of Nutrition, Harvard School of Public Health Boston, MA

When one estimates the effects of a polytomous exposure, it is common practice to express all effects relative to a baseline or reference level. Certain authors have challenged this practice and proposed alternatives, which we review here. One alternative, the "floating absolute risk" method, can supply useful statistics and trend graphs, but it does not yield valid confidence intervals for relative risks. All categorical methods have further shortcomings when the exposure is continuous, however. These shortcomings can be addressed by plotting or tabulating confidence limits for points on a flexible curve fitted to the uncategorized data. Am J Epidemiol 1999; 149: 1077—86.

biometry; dose-response; epidemiologic methods; relative risk; smoothing; trend analysis


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