Causation and Causal Inference in Epidemiology

American Journal of Public Health, Vol. 95, No. S1, pp. S144-S150, 2005

The Coronado Conference: Scientific Evidence and Public Policy Paper

7 Pages Posted: 30 Nov 2005

See all articles by Kenneth Rothman

Kenneth Rothman

Boston University School of Public Health - Department of Epidemiology

Sander Greenland

University of California, Los Angeles (UCLA) - Department of Statistics

Abstract

Concepts of cause and causal inference are largely self-taught from early experiences. A model of causation that describes causes in terms of sufficient causes and their component causes illuminates important principles such as multicausality, the dependence of the strength of component causes on the prevalence of complementary component causes, and interaction between component causes. Philosophers agree that causal propositions cannot be proved and find flaws or practical limitations in all philosophies of causal inference. Hence, the role of logic, belief, and observation in evaluating causal propositions is not settled. Causal inference in epidemiology is better viewed as an exercise in measurement of an effect than as a criterion-guided process for deciding whether an effect is present or not.

Keywords: Scientific evidence, Causation

JEL Classification: K13, K32

Suggested Citation

Rothman, Kenneth and Greenland, Sander, Causation and Causal Inference in Epidemiology. American Journal of Public Health, Vol. 95, No. S1, pp. S144-S150, 2005, The Coronado Conference: Scientific Evidence and Public Policy Paper, Available at SSRN: https://ssrn.com/abstract=849605

Kenneth Rothman (Contact Author)

Boston University School of Public Health - Department of Epidemiology ( email )

715 Albany Street
Boston, MA 02118
United States

Sander Greenland

University of California, Los Angeles (UCLA) - Department of Statistics ( email )

8125 Math Sciences
UCLA
Los Angeles, CA 90095
United States

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