The DOI matches its Crossref record; 46 of the 49 references it cites were found in a registry or an index.
An Axiomatic Characterization of Causal Counterfactuals
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“Galles and Pearl [1] and Halpern [2] have given a complete axiomatization of structural counterfactuals, embracing both recursive and non-recursive models”
From The Deductive Approach to Causal Inference (2014) · cites this paper as [1]
Citations
Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · Journal of Educational Psychology · doi:10.1037/h0037350 · Cited by 9,436
Statistics and Causal Inference
Holland, P. W. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478354 · Cited by 5,293
Causation, Prediction, and Search
Spirtes, P., Glymour, C., & Scheines, R. (1993) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2748-9 · Cited by 4,617
Identification of Causal Effects Using Instrumental Variables
Angrist, J. D., Imbens, G. W., & Rubin, D. B. (1996) · Journal of the American Statistical Association · doi:10.1080/01621459.1996.10476902 · Cited by 4,230
Halpern, J. Y. (1994) · Mathematical Social Sciences · doi:10.1016/0165-4896(94)90005-1 · Cited by 3,620
The Central Role of the Propensity Score in Observational Studies for Causal Effects
Rosenbaum, P. R., & Rubin, D. B. (1983) · Biometrika · doi:10.2307/2335942 · Cited by 3,495
Fagin, R., Halpern, J. Y., Moses, Y. O., & Vardi, M. Y. (1995) · The MIT Press eBooks · doi:10.7551/mitpress/5803.001.0001 · Cited by 2,612
Robins, J. (1986) · Mathematical Modelling · doi:10.1016/0270-0255(86)90088-6 · Cited by 2,451
Causal diagrams for empirical research
PEARL, J. (1995) · Biometrika · doi:10.1093/biomet/82.4.669 · Cited by 2,355 · cited 11×
“[Balke and Pearl, 1995] A. Balke and J. Pearl.”
BackgroundMethodInfluentialSelf-citation
Research works printed but not linked: 8
- R.J. Bowden and D.A. Turkington (1984), Instrumental Variables. Cambridge University Press, Cambridge, MA.
- A.P. Dawid (1997), Causal inference without counterfactuals. Technical Report, Department of Statistical Science, University College London, UK.
- P.J. Dhrymcs (1970), Economctrics. Springer-Verlag, New York.
- D. Galles and J. Pearl (1997a) An axiomatic characterization of causal counterfactuals. Technical Report R-250-L, Computer Science Department, University of California, Los Angeles, March 1997. Prepared for Foundations of Science, Kluwer Academic Publishers.
- Arthur S. Goldberger (1992), ‘Models of substance [comment on N. Wermuth, “On block-recursive linear regression equations”]’. Brazilian Journal of Probability and Statistics, 6:1–56.
- D. Lewis (1973b), Counterfactuals. Harvard University Press, Cambridge, MA.
- J. Pearl (1988), Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann San Mateo, CA. (Revised 2nd printing, 1992).
- J. Pearl (1997a), “The new challenge: From a century of statistics to an age of causation.’ Computing Science and Statistics, 29(2):415–423.
Cited by
Sorted by citations
Air Pollution and Hospital Admissions for Heart Disease in Eight U.S. Counties
Schwartz, J. D. (1999) · Epidemiology · doi:10.1097/00001648-199901000-00005 · Cited by 3,045
Confounding and Collapsibility in Causal Inference
Greenland, S., Pearl, J., & Robins, J. M. (1999) · Statistical Science · doi:10.1214/ss/1009211805 · Cited by 933
Self-citationEight Myths About Causality and Structural Equation Models
Bollen, K. A., & Pearl, J. (2013) · Handbooks of sociology and social research · doi:10.1007/978-94-007-6094-3_15 · Cited by 680
“A systematic analysis of the syntax and semantics of the two notational systems reveals that they are logically equivalent (Galles and Pearl 1998; Halpern 1998); a theorem in one is a theorem in the other, and an assumption in one has a parallel interpretation in the other.”
Self-citationCausal Parameters and Policy Analysis in Economics: A Twentieth Century Retrospective*
Heckman, J. J. (2000) · The Quarterly Journal of Economics · doi:10.1162/003355300554674 · Cited by 507
Causal inference and the data-fusion problem
Bareinboim, E., & Pearl, J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510507113 · Cited by 621
Self-citation
Metadata
- Authors
- Galles, D., & Pearl, J.
- Affiliations
- University of California, Los Angeles (US)
- Venue
- Foundations of Science
- Published
- 1998-01
- Volume
- 3
- Issue
- 1
- Pages
- 151-182
- ISSN
- 1233-1821 (ISSN-L)
- 1572-8471
- OpenAlex
- W1576238869
- Cited by
- 192
- References
- 49
- Citations by year
- 2026: 4 · 2025: 14 · 2024: 11 · 2023: 9 · 2022: 19 · 2021: 13 · 2020: 10 · 2019: 25 · 2018: 5 · 2017: 4 · 2016: 6 · 2015: 10 · 2014: 8 · 2013: 7 · 2012: 10
- FWCI
- 7.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Foundations of Science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Keywords
- counterfactuals, composition properties, reversibility, feedback, probabilistic graphical models, causal inference, axiomatization
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