Counterfactuals and Causal Inference - Info and Reading Options
By Stephen L. Morgan

"Counterfactuals and Causal Inference" was published by Cambridge University Press in 2015, it has 499 pages and the language of the book is English.
“Counterfactuals and Causal Inference” Metadata:
- Title: ➤ Counterfactuals and Causal Inference
- Author: Stephen L. Morgan
- Language: English
- Number of Pages: 499
- Publisher: Cambridge University Press
- Publish Date: 2015
“Counterfactuals and Causal Inference” Subjects and Themes:
- Subjects: ➤ Causation - Research - Methodology - Social sciences - Social sciences, research - Social sciences, methodology - MATHEMATICS / Probability & Statistics / General - Social sciences--research - Social sciences--methodology - Mathematics--probability & statistics--general - H62 .m646 2015 - 300.72 - Mat029000 - MATHEMATICS - Probability & Statistics - General
Edition Specifications:
- Format: Paperback
Edition Identifiers:
- The Open Library ID: OL27305965M - OL14874567W
- Online Computer Library Center (OCLC) ID: 890080248
- Library of Congress Control Number (LCCN): 2014033205
- ISBN-13: 9781107694163
- All ISBNs: 9781107694163
AI-generated Review of “Counterfactuals and Causal Inference”:
"Counterfactuals and Causal Inference" Description:
The Open Library:
"In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed"--
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