On the role of counterfactuals in inferring causal effects

Foundations of Science 9 (1):65-101 (2004)
Abstract
Causal inference in the empiricalsciences is based on counterfactuals. The mostcommon approach utilizes a statistical model ofpotential outcomes to estimate causal effectsof treatments. On the other hand, one leadingapproach to the study of causation inphilosophical logic has been the analysis ofcausation in terms of counterfactualconditionals. This paper discusses and connectsboth approaches to counterfactual causationfrom philosophy and statistics. Specifically, Ipresent the counterfactual account of causationin terms of Lewis's possible-world semantics,and reformulate the statistical potentialoutcome framework using counterfactualconditionals. This procedure highlights variousproperties and mechanisms of the statisticalmodel.
Keywords Philosophy   Philosophy of Science   Mathematical Logic and Foundations   Methodology of the Social Sciences
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DOI 10.1023/B:FODA.0000014881.82061.7b
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