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

By: Contributor(s): Material type: TextTextSeries: Analytical methods for social researchPublication details: New York : Cambridge University Press, 2007.Description: 1 online resource (xiii, 319 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780511350122
  • 0511350120
  • 0511349262
  • 9780511349263
  • 9780511804564
  • 0511804563
  • 9780511348297
  • 0511348290
Subject(s): Genre/Form: Additional physical formats: Print version:: Counterfactuals and causal inference.DDC classification:
  • 300.72 22
LOC classification:
  • H62 .M646 2007
Other classification:
  • 70.03
  • QH 253
Online resources:
Contents:
Part I. Counterfactual Causality and Empirical Research in the Social Sciences -- 1. Introduction -- 2. The counterfactual model; Part II. Estimating Causal Effects by Conditioning -- 3. Causal graphs, identification, and models of causal exposure -- 4. Matching estimators of causal effects -- 5. Regression estimators of causal effects -- Part III. Estimating Causal Effects When Simple Conditioning is Ineffective -- 6. Identification in the absence of a complete model of causal exposure -- 7. Natural experiments and instrumental variables -- 8. Mechanisms and causal explanation -- 9. Repeated observations and the estimation of causal effects -- Part IV. Conclusions -- 10. Counterfactual causality and future empirical research in the social sciences.
Review: "In this book, the counterfactual model of causality for observational data analysis is presented, and methods for causal effect estimation are demonstrated using examples from sociology, political science, and economics."--Jacket
Item type:
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Includes bibliographical references (pages 291-316) and index.

Part I. Counterfactual Causality and Empirical Research in the Social Sciences -- 1. Introduction -- 2. The counterfactual model; Part II. Estimating Causal Effects by Conditioning -- 3. Causal graphs, identification, and models of causal exposure -- 4. Matching estimators of causal effects -- 5. Regression estimators of causal effects -- Part III. Estimating Causal Effects When Simple Conditioning is Ineffective -- 6. Identification in the absence of a complete model of causal exposure -- 7. Natural experiments and instrumental variables -- 8. Mechanisms and causal explanation -- 9. Repeated observations and the estimation of causal effects -- Part IV. Conclusions -- 10. Counterfactual causality and future empirical research in the social sciences.

"In this book, the counterfactual model of causality for observational data analysis is presented, and methods for causal effect estimation are demonstrated using examples from sociology, political science, and economics."--Jacket

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