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The Deductive Approach to Causal Inference

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  • Pearl Judea

    (Department of Computer Science, University of California – Los Angeles, Los Angeles, CA, 90095-1596, USA)

Abstract

This paper reviews concepts, principles, and tools that have led to a coherent mathematical theory that unifies the graphical, structural, and potential outcome approaches to causal inference. The theory provides solutions to a number of pending problems in causal analysis, including questions of confounding control, policy analysis, mediation, missing data, and the integration of data from diverse studies.

Suggested Citation

  • Pearl Judea, 2014. "The Deductive Approach to Causal Inference," Journal of Causal Inference, De Gruyter, vol. 2(2), pages 1-15, September.
    • Handle: RePEc:bpj:causin:v:2:y:2014:i:2:p:15:n:5
    DOI: 10.1515/jci-2014-0016
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    References listed on IDEAS

    as
    1. Manabu Kuroki & Judea Pearl, 2014. "Measurement bias and effect restoration in causal inference," Biometrika, Biometrika Trust, vol. 101(2), pages 423-437.
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