US EPA

2325145 

Journal Article 

Causation and causal inference in epidemiology 

Rothman, KJ; Greenland, S 

2005 

Yes 

American Journal of Public Health
ISSN: 0090-0036
EISSN: 1541-0048 

95 Suppl 1 

S144-S150 

English 

16030331 

10.2105/AJPH.2004.059204 

Concepts of cause and causal inference are largely self-taught from early learning experiences. A model of causation that describes causes in terms of sufficient causes and their component causes illuminates important principles such as multi-causality, 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 rather than as a criterion-guided process for deciding whether an effect is present or not.