Causality (book)

Causality: Models, Reasoning, and Inference (2000;[1] updated 2009[2]) is a book by Judea Pearl.[3] It is an exposition and analysis of causality.[4][5] It is considered to have been instrumental in laying the foundations of the modern debate on causal inference in several fields including statistics, computer science and epidemiology.[6] In this book, Pearl espouses the Structural Causal Model (SCM) that uses structural equation modeling.[7] This model is a competing viewpoint to the Rubin causal model. Some of the material from the book was reintroduced in the more general-audience targeting The Book of Why.

Causality: Models, Reasoning, and Inference
AuthorJudea Pearl
LanguageEnglish
SubjectCausality
PublisherCambridge University Press
Publication date
2000, 2009
Pages484
ISBN978-0521895606

Reviews

Pearl succeeds in bringing together in a general nonparametric framework the counterfactual tradition of causal analysis with the variants of structural equation modeling worth keeping. The graph theory that he uses to accomplish this fusion is often elegant. Thus, Causality is a major statement, which all who claim to know what causality is must read.

— Stephen L. Morgan (2004)[8]

The book gave Pearl the 2001 Lakatos Award in Philosophy of Science.[9]

See also

References
  1. Judea Pearl (2000). Causality: Models, Reasoning and Inference. Cambridge University Press. ISBN 978-0-521-77362-1. OL 15495862M. Wikidata Q108441215.
  2. Judea Pearl (2009). Causality (2nd ed.). New York City: Cambridge University Press. ISBN 978-0-521-89560-6. OCLC 1261134347. OL 27305967M. Wikidata Q108441243.
  3. Pearl, Judea (June 18, 2009). "Giving Computers Free Will". Forbes. Archived from the original on January 12, 2020. Retrieved January 12, 2020.
  4. McArdle, Megan (May 11, 2012). "When Correlation Is Not Causation, But Something Much More Screwy". The Atlantic. Archived from the original on August 18, 2019. Retrieved January 12, 2020.
  5. Chin, Matthew (July 22, 2016). "Solving big data's 'fusion' problem". UCLA. Archived from the original on October 16, 2019. Retrieved January 12, 2020.
  6. Porta, Miquel (October 17, 2014). "The deconstruction of paradoxes in epidemiology". OUPblog. Archived from the original on September 26, 2019. Retrieved January 12, 2020.
  7. Hoover, K. (2003). The Economic Journal, 113(488), F411–F413. Retrieved from https://www.jstor.org/stable/3590225
  8. Morgan, Stephen L. "Invited review of Causality: Models, Reasoning, and Evidence by Judea Pearl". Sociological Methods & Research. 32 (2): 411–416. doi:10.1177/0049124104323004. S2CID 220533962.
  9. Leland Gerson Neuberg (June 6, 2003). "CAUSALITY: MODELS, REASONING, AND INFERENCE, by Judea Pearl, Cambridge University Press, 2000". Econometric Theory. 19 (4). doi:10.1017/S0266466603004109. ISSN 0266-4666. Wikidata Q108441284.
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