Inferring causation in epidemiology: Mechanisms, black boxes, and contrasts

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

49 Citations (Scopus)

Abstract

This chapter explores the idea that causal inference is warranted if and only if the mechanism underlying the inferred causal association is identified. This mechanistic stance is discernible in the epidemiological literature, and in the strategies adopted by epidemiologists seeking to establish causal hypotheses. But the exact opposite methodology is also discernible, the black box stance, which asserts that epidemiologists can and should make causal inferences on the basis of their evidence, without worrying about the mechanisms that might underlie their hypotheses. This chapter argues that the mechanistic stance is indeed a bad methodology for causal inference. However, this chapter detaches and defends a mechanistic interpretation of causal generalisations in epidemiology as existence claims about underlying mechanisms.

Original languageEnglish
Title of host publicationCausality in the Sciences
PublisherOxford University Press
ISBN (Electronic)9780191728921
ISBN (Print)9780199574131
DOIs
Publication statusPublished - 22 Sept 2011

Keywords

  • Causal inference
  • Causality
  • Causation
  • Contrast
  • Epidemiology
  • Mechanism
  • Risk factor

ASJC Scopus subject areas

  • General Mathematics

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