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American Journal of Epidemiology Advance Access originally published online on August 24, 2005
American Journal of Epidemiology 2005 162(7):618-620; doi:10.1093/aje/kwi255
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American Journal of Epidemiology Copyright © 2005 by the Johns Hopkins Bloomberg School of Public Health All rights reserved

ORIGINAL CONTRIBUTIONS

Invited Commentary: Hypothetical Interventions to Define Causal Effects—Afterthought or Prerequisite?

Miguel A. Hernán

From the Department of Epidemiology, Harvard School of Public Health, Boston, MA

Correspondence to Dr. Miguel A. Hernán, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115 (e-mail: miguel_hernan@post.harvard.edu).

Received for publication May 23, 2005. Accepted for publication May 26, 2005.

The first 150 words of the full text of this article appear below.

"It is philosophy, not science." Physicists are familiar with this criticism of string theory, a theory that provides a unified description of all forces operating in the universe (1Go). Unlike philosophical arguments, scientific theories or their predictions need to be confirmed empirically. String theory involves an elegant set of mathematical equations; unfortunately, it is unclear whether its predictions are, or will be, testable—not a small obstacle for a "theory of everything."

Some of the string theorists' tribulations regarding untestable predictions are shared by epidemiologists and other researchers who use counterfactual theory to draw causal inferences from observational data. I do not mean that epidemiologists are limited by the practical impossibility of conducting certain subatomic experiments. Rather, I refer to a fundamental shortcoming of causal inference from observational data in certain settings: the absence of a well-defined causal effect. When the causal effect of interest is ill defined, the counterfactual . . . [Full Text of this Article]


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