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Causal inference for statistics, soc...
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Imbens, Guido,
Causal inference for statistics, social, and biomedical sciences :an introduction /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Causal inference for statistics, social, and biomedical sciences :Guido W. Imbens (Stanford University), Donald B. Rubin (Harvard University)
其他題名:
an introduction /
作者:
Imbens, Guido,
其他作者:
Rubin, Donald B.
出版者:
New York :Cambridge University Press,2015.
面頁冊數:
xix, 625 p. :ills. ;26 cm.
標題:
Social sciencesResearch.
ISBN:
9780521885881
Causal inference for statistics, social, and biomedical sciences :an introduction /
Imbens, Guido,
Causal inference for statistics, social, and biomedical sciences :
an introduction /Guido W. Imbens (Stanford University), Donald B. Rubin (Harvard University) - New York :Cambridge University Press,2015. - xix, 625 p. :ills. ;26 cm.
Includes bibliographical references (pages 591-604) and indexes.
Part I. Introduction; 1. Causality: the basic framework -- 2. A brief history of the potential-outcome approach to causal inference; 3. A Classification of assignment mechanisms --
ISBN: 9780521885881
LCCN: 2014020988Subjects--Topical Terms:
178448
Social sciences
--Research.
LC Class. No.: H62 / .I537 2015
Dewey Class. No.: 519.54
Causal inference for statistics, social, and biomedical sciences :an introduction /
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Part I. Introduction; 1. Causality: the basic framework -- 2. A brief history of the potential-outcome approach to causal inference; 3. A Classification of assignment mechanisms --
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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 --
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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 --
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Part IV. Regular Assignment Mechanisms: Analysis; 17. Subclassification on the propensity score -- 18. Matching estimators (Card-Krueger data) -- 19. A general method for estimating sampling variances for standard estimators for average causal effects -- 20. Inference for general causal estimands.
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Part V. Regular Assignment Mechanisms: Supplementary Analyses; 21. Assessing unconfoundedness -- 22. Sensitivity analysis and bounds --
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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 analysis in instrumental variable settings: randomized experiments with two-sided noncompliance.
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Part VII. Conclusion; 26. Conclusions and extensions.
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