Counterfactuals and Causal Inference: Methods and Principles for Social Research

ISBN: 9780521671934 出版年：2007 页码：335 Morgan Winship Cambridge University Press

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.