European Journal of Epidemiology

, Volume 31, Issue 10, pp 1065–1066 | Cite as

Tyler J VanderWeele. Explanation in causal inference: methods for mediation and interaction

Oxford University Press, 2015
  • Ashley I. Naimi

The field of epidemiology is primarily concerned with evaluating cause-effect relationships. Research questions are often first articulated informally using (e.g.) English language sentences. For example, “what is the effect of smoking on cardiovascular disease risk, irrespective of smoking’s effect on body weight?” To answer this question, data are collected and entered into a computer, which performs a number of mathematical operations with the data to yield a number, usually interpreted as the answer to the research question of interest.

Robins long ago noted a problem with the relation between the (e.g.) English language research questions asked by epidemiologists, and the computer calculations that yield results interpreted as cause-effect relations [1]. On the one hand, the computer calculations are based on rigorously defined mathematical objects. On the other hand, the English language sentences conveying cause-effect relations are often ambiguous. Causal inference was...


Main Text Causal Inference Interaction Analysis Mathematical Operation Epidemiologic Method 
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  1. 1.
    Robins JM. Addendum to “a new approach to causal inference in mortality studies with a sustained exposure period-application to control of the healthy worker survivor effect”. Math Model. 1987;14(9–12):923–45.Google Scholar
  2. 2.
    VanderWeele TJ. Explanation in causal inference: methods for mediation and interaction. Oxford: Oxford University Press; 2015.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Epidemiology, Graduate School of Public HealthUniversity of PittsburghPittsburghUSA

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