《Causal Inference for Statistics, Social, and Biomedical Sciences》
Causal Inference for Statistics, Social, and Biomedical Sciencestxt,chm,pdf,epub,mobi下载
作者: Guido W. Imbens / Donald B. Rubin
出版社: Cambridge University Press
副标题: An Introduction
出版年: 2015-4-6
页数: 644
定价: GBP 40.99
装帧: Hardcover
ISBN: 9780521885881
1. The basic framework: potential outcomes, stability, and the assignment mechanism
2. A brief history of the potential-outcome approach to causal inference
3. A taxonomy of assignment mechanisms
Part II. Classical Randomized Experiments:
4. A taxonomy of classical randomized experiments
· · · · · · ()
Part I. Introduction:
1. The basic framework: potential outcomes, stability, and the assignment mechanism
2. A brief history of the potential-outcome approach to causal inference
3. A taxonomy of assignment mechanisms
Part II. Classical Randomized Experiments:
4. A taxonomy of classical randomized experiments
5. Fisher's exact P-values for completely randomized experiments
6. Neyman's repeated sampling approach to completely randomized experiments
7. Regression methods for completely randomized experiments
8. Model-based inference in completely randomized experiments
9. Stratified randomized experiments
10. Paired randomized experiments
11. Case study: an experimental evaluation of a labor-market program
Part III. Regular Assignment Mechanisms: Design:
12. Unconfounded treatment assignment
13. Estimating the propensity score
14. Assessing overlap in covariate distributions
15. Design in observational studies: matching to ensure balance in covariate distributions
16. Design in observational studies: trimming to ensure balance in covariate distributions
Part IV. Regular Assignment Mechanisms: Analysis:
17. Subclassification on the propensity score
18. Matching estimators (Card-Krueger data)
19. Estimating the variance of estimators under unconfoundedness
20. Alternative estimands
Part V. Regular Assignment Mechanisms: Supplementary Analyses:
21. Assessing the unconfoundedness assumption
22. Sensitivity analysis and bounds
Part VI. Regular Assignment Mechanisms with Noncompliance: Analysis:
23. Instrumental-variables analysis of randomized experiments with one-sided noncompliance
24. Instrumental-variables analysis of randomized experiments with two-sided noncompliance
25. Model-based analyses with instrumental variables
Part VII. Conclusion:
26. Conclusions and extensions.
· · · · · · ()
作者: Guido W. Imbens / Donald B. Rubin
出版社: Cambridge University Press
副标题: An Introduction
出版年: 2015-4-6
页数: 644
定价: GBP 40.99
装帧: Hardcover
ISBN: 9780521885881
内容简介 · · · · · ·
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be r...
目录 · · · · · ·
Part I. Introduction:1. The basic framework: potential outcomes, stability, and the assignment mechanism
2. A brief history of the potential-outcome approach to causal inference
3. A taxonomy of assignment mechanisms
Part II. Classical Randomized Experiments:
4. A taxonomy of classical randomized experiments
· · · · · · ()
Part I. Introduction:
1. The basic framework: potential outcomes, stability, and the assignment mechanism
2. A brief history of the potential-outcome approach to causal inference
3. A taxonomy of assignment mechanisms
Part II. Classical Randomized Experiments:
4. A taxonomy of classical randomized experiments
5. Fisher's exact P-values for completely randomized experiments
6. Neyman's repeated sampling approach to completely randomized experiments
7. Regression methods for completely randomized experiments
8. Model-based inference in completely randomized experiments
9. Stratified randomized experiments
10. Paired randomized experiments
11. Case study: an experimental evaluation of a labor-market program
Part III. Regular Assignment Mechanisms: Design:
12. Unconfounded treatment assignment
13. Estimating the propensity score
14. Assessing overlap in covariate distributions
15. Design in observational studies: matching to ensure balance in covariate distributions
16. Design in observational studies: trimming to ensure balance in covariate distributions
Part IV. Regular Assignment Mechanisms: Analysis:
17. Subclassification on the propensity score
18. Matching estimators (Card-Krueger data)
19. Estimating the variance of estimators under unconfoundedness
20. Alternative estimands
Part V. Regular Assignment Mechanisms: Supplementary Analyses:
21. Assessing the unconfoundedness assumption
22. Sensitivity analysis and bounds
Part VI. Regular Assignment Mechanisms with Noncompliance: Analysis:
23. Instrumental-variables analysis of randomized experiments with one-sided noncompliance
24. Instrumental-variables analysis of randomized experiments with two-sided noncompliance
25. Model-based analyses with instrumental variables
Part VII. Conclusion:
26. Conclusions and extensions.
· · · · · · ()
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