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Causation and causal inference 

Causation and causal inference
Chapter:
Causation and causal inference
Author(s):

Katherine J. Hoggatt

and Sander Greenland

DOI:
10.1093/med/9780199218707.003.0038
Page of

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date: 19 September 2020

This chapter offers an introduction to causal inference theory as relevant to public health research. Causal inference can be viewed as a prediction problem, addressing the question of what the likely outcome under one action vs. an alternative action is. Although asking these types of questions is very natural, answering them requires careful thought in both the statement of the causal hypothesis and the techniques used to attempt an answer. This chapter discusses these complexities, with further discussion in Chapter 6.12 (‘Validity and bias in epidemiological research’). More thorough coverage of these issues can be found in Chapters 2, 4, and 9 of Rothman et al. (2008).

The chapter reviews considerations that have been invoked in discussions of causality based on epidemiologic evidence. It then describes the potential-outcome (counterfactual) framework for cause and effect, showing how measures of effect and association are distinguished in that framework. The framework illustrates problems inherent in attempts to quantify the changes in health expected under different actions or interventions. The chapter concludes with a discussion of how research findings may be translated into policy.

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