Direct and Indirect Causal Effects via Potential Outcomes*
Abstract
The use of the concept of ‘direct’ versus ‘indirect’ causal effects is common, not only in statistics but also in many areas of social and economic sciences. The related terms of ‘biomarkers’ and ‘surrogates’ are common in pharmacological and biomedical sciences. Sometimes this concept is represented by graphical displays of various kinds. The view here is that there is a great deal of imprecise discussion surrounding this topic and, moreover, that the most straightforward way to clarify the situation is by using potential outcomes to define causal effects. In particular, I suggest that the use of principal stratification is key to understanding the meaning of direct and indirect causal effects. A current study of anthrax vaccine will be used to illustrate ideas.
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Approaching the mediation problem from an exclusivist potential-outcome viewpoint, void of structural guidance, leads to counterintuitive definitions labeled principal stratification that are at variance with common understanding of direct and indirect effects.
“In contrast, when the mediation problem is approached from an exclusivist potential-outcome viewpoint, void of the structural guidance of Eq. ( 29), counterintuitive definitions ensue, carrying the label”
From An Introduction to Causal Inference (2010) · cites this paper as Rubin, 2004
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“Nevertheless, I still feel as I did in my discussion with Imbens (Imbens & Rubin, 1995) of Pearl (1995) , that the framework is inherently less revealing than the potential outcomes framework because it tends to bury essential scientific and design issues.”
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“22According to Rubin (2004, 2005), R.A. Fisher made this mistake in the context of agriculture experiments.”
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Generating Digital Twins with Multiple Sclerosis Using Probabilistic Neural Networks
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- Authors
- Rubin, D. B.
- Affiliations
- Harvard University (US)
- Corresponding author
- Rubin, Donald B.
- ORCID
- Rubin, Donald B.
- Venue
- Scandinavian Journal of Statistics
- Publisher
- Wiley
- Published
- 2004-05-19
- Volume
- 31
- Issue
- 2
- Pages
- 161-170
- ISSN
- 0303-6898 (ISSN-L)
- 1467-9469
- OpenAlex
- W1973627705
- Cited by
- 324
- References
- 6
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 11 · 2023: 15 · 2022: 4 · 2021: 15 · 2020: 16 · 2019: 13 · 2018: 13 · 2017: 9 · 2016: 16 · 2015: 21 · 2014: 16 · 2013: 19 · 2012: 24
- FWCI
- 11.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Scandinavian Journal of Statistics (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- potential outcomes, principal stratification, biomarkers, surrogates, causal inference, anthrax vaccine, causal graphical models
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