2000 CausalityModelsReasoningandInfe
- (Pearl, 2000) ⇒ Judea Pearl. (2000). “Causality: Models, Reasoning and Inference.” Cambridge University Press.
Subject Headings: Causal Analysis, Structural Causal Model (SCM), Causal Inference, Structural Equation Modeling.
Notes
Cited By
- http://scholar.google.com/scholar?q=%222009%22+Causality%3A+Models%2C+Reasoning+and+Inference
- http://dl.acm.org/citation.cfm?id=1642718&preflayout=flat
2018
- (Pearl & Mackenzie, 2018) ⇒ Judea Pearl, and Dana Mackenzie. (2018). “The Book of Why: The New Science of Cause and Effect.” Hachette UK. ISBN:9780465097609
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Causality_(book) Retrieved:2017-11-10.
- Causality: Models, Reasoning and Inference (2000; updated 2009) is a book by Judea Pearl . It is an exposition and analysis of causality. 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. In this book, Pearl espouses the Structural Causal Model (SCM) that uses structural equation modeling. This model is a competing viewpoint to the Rubin causal model.
Quotes
Book Overview
Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. The book will open the way for including causal analysis in the standard curricula of statistics, artificial intelligence, business, epidemiology, social sciences, and economics. Students in these fields will find natural models, simple inferential procedures, and precise mathematical definitions of causal concepts that traditional texts have evaded or made unduly complicated. The first edition of Causality has led to a paradigmatic change in the way that causality is treated in statistics, philosophy, computer science, social science, and economics. Cited in more than 3,000 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. … Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2000 CausalityModelsReasoningandInfe | Judea Pearl | Causality: Models, Reasoning and Inference | 2000 |