Counterfactuals and causal inference : methods and principles for social research By: Stephen L.Morgan; Christopher Winship
Material type:
TextLanguage: English Publication details: New Delhi Cambridge University Press 2015Edition: 2ndDescription: 499 P.BISBN: - 9781107694163
- 300.72 MOR(COU)Ed2
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Reference PhD Research
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SXU PhD Library Reference Section | Reference | R 300.72 MOR(COU)Ed2 (Browse shelf(Opens below)) | 568 | Not For Loan | 568 | |
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| 300.72 GUT(BAS).C1 Basic Research Methods An Entry to Social Science Research | 300.72 KUM(RES)Ed2 Research Methodology | 300.72 KUM(RES)Ed2.C1 Research Methodology | 300.72 MOR(COU)Ed2 Counterfactuals and causal inference : methods and principles for social research | 300.721 BAZ(QUA)Ed2 Qualitative Data Analysis : practical strategies | 300.721 BAZ(QUA)Ed2.C1 Qualitative Data Analysis : practical strategies | 300.721 BAZ(QUA)Ed2.C2 Qualitative Data Analysis : practical strategies |
Part 1. Causality and empirical research in the social sciences. Introduction
Part 2. Counterfactuals, potential outcomes, and causal graphs. Counterfactuals and the potential outcome model
Causal graphs
Part 3. Estimating causal effects by conditioning on observed variables to block back-door paths
Matching estimators of causal effects
Regression estimators of causal effects
Weighted regression estimators of causal effects
Part 4. Estimating causal effects when back-door conditioning is ineffective. Self-selection, heterogeneity, and causal graphs
Instrumental variable estimators of causal effects
Mechanisms and causal explanation
Repeated observations and the estimation of causal effects
Part 5. Estimation when causal effects are not point-identified by observables. Distributional assumptions, set identification, and sensitivity analysis
Part 6. Conclusions. Counterfactuals and the future of empirical research in observational social science
References
Index
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