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The Resource Counterfactuals and causal inference : methods and principles for social research, Stephen L. Morgan, Christopher Winship

Counterfactuals and causal inference : methods and principles for social research, Stephen L. Morgan, Christopher Winship

Label
Counterfactuals and causal inference : methods and principles for social research
Title
Counterfactuals and causal inference
Title remainder
methods and principles for social research
Statement of responsibility
Stephen L. Morgan, Christopher Winship
Creator
Contributor
Author
Subject
Language
eng
Summary
"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".--
Member of
Assigning source
Provided by Publisher
Cataloging source
DEBSZ
http://library.link/vocab/creatorDate
1971-
http://library.link/vocab/creatorName
Morgan, Stephen L.
Index
no index present
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
Winship, Christopher
Series statement
Analytical methods for social research
http://library.link/vocab/subjectName
  • Social sciences
  • Social sciences
  • Causation
Label
Counterfactuals and causal inference : methods and principles for social research, Stephen L. Morgan, Christopher Winship
Link
https://opac.eui.eu/client/en_GB/default/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:436439/one
Instantiates
Publication
Note
Revised edition of the authors' Counterfactuals and causal inference, published in 2007. - Includes bibliographical references and index
Contents
Part I. Causality and Empirical Research in the Social Sciences: 1. Introduction; Part II. Counterfactuals, Potential Outcomes, and Causal Graphs: 2. Counterfactuals and the potential-outcome model; 3. Causal graphs; Part III. Estimating Causal Effects by Conditioning on Observed Variables to Block Backdoor Paths: 4. Models of causal exposure and identification criteria for conditioning estimators; 5. Matching estimators of causal effects; 6. Regression estimators of causal effects; 7. Weighted regression estimators of causal effects; Part IV. Estimating Causal Effects When Backdoor Conditioning is Ineffective: 8. Self-selection, heterogeneity, and causal graphs; 9. Instrumental-variable estimators of causal effects; 10. Mechanisms and causal explanation; 11. Repeated observations and the estimation of causal effects; Part V. Estimation When Causal Effects Are Not Point Identified by Observables: 12. Distributional assumptions, set identification, and sensitivity analysis; Part VI. Conclusions: 13. Counterfactuals and the future of empirical research in observational social science
Control code
FIEb17646716
Dimensions
25 cm.
Edition
2. edition.
Extent
xxiii, 499 pages
Isbn
9781107065079
System control number
(OCoLC)897146492
Label
Counterfactuals and causal inference : methods and principles for social research, Stephen L. Morgan, Christopher Winship
Link
https://opac.eui.eu/client/en_GB/default/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:436439/one
Publication
Note
Revised edition of the authors' Counterfactuals and causal inference, published in 2007. - Includes bibliographical references and index
Contents
Part I. Causality and Empirical Research in the Social Sciences: 1. Introduction; Part II. Counterfactuals, Potential Outcomes, and Causal Graphs: 2. Counterfactuals and the potential-outcome model; 3. Causal graphs; Part III. Estimating Causal Effects by Conditioning on Observed Variables to Block Backdoor Paths: 4. Models of causal exposure and identification criteria for conditioning estimators; 5. Matching estimators of causal effects; 6. Regression estimators of causal effects; 7. Weighted regression estimators of causal effects; Part IV. Estimating Causal Effects When Backdoor Conditioning is Ineffective: 8. Self-selection, heterogeneity, and causal graphs; 9. Instrumental-variable estimators of causal effects; 10. Mechanisms and causal explanation; 11. Repeated observations and the estimation of causal effects; Part V. Estimation When Causal Effects Are Not Point Identified by Observables: 12. Distributional assumptions, set identification, and sensitivity analysis; Part VI. Conclusions: 13. Counterfactuals and the future of empirical research in observational social science
Control code
FIEb17646716
Dimensions
25 cm.
Edition
2. edition.
Extent
xxiii, 499 pages
Isbn
9781107065079
System control number
(OCoLC)897146492

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