Observation and Experiment : : An Introduction to Causal Inference / / Paul R. Rosenbaum.

In the face of conflicting claims about some treatments, behaviors, and policies, the question arises: What is the most scientifically rigorous way to draw conclusions about cause and effect in the study of humans? In this introduction to causal inference, Paul Rosenbaum explains key concepts and me...

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Bibliographic Details
Superior document:Title is part of eBook package: De Gruyter Harvard University Press Complete eBook-Package 2017
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Place / Publishing House:Cambridge, MA : : Harvard University Press, , [2018]
©2017
Year of Publication:2018
Language:English
Online Access:
Physical Description:1 online resource (400 p.) :; 13 graphs, 28 tables
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Other title:Frontmatter --
Contents --
Preface --
Reading Options --
List of Examples --
Part I. Randomized Experiments --
1. A Randomized Trial --
2. Structure --
3. Causal Inference in Randomized Experiments --
4. Irrationality and Polio --
Part II. Observational Studies --
5. Between Observational Studies and Experiments --
6. Natural Experiments --
7. Elaborate Theories --
8. Quasi-experimental Devices --
9. Sensitivity to Bias --
10. Design Sensitivity --
11. Matching Techniques --
12. Biases from General Dispositions --
13. Instruments --
14. Conclusion --
Appendix: Bibliographic Remarks --
Notes --
Glossary: Notation and Technical Terms --
Suggestions for Further Reading --
Acknowledgments --
Index
Summary:In the face of conflicting claims about some treatments, behaviors, and policies, the question arises: What is the most scientifically rigorous way to draw conclusions about cause and effect in the study of humans? In this introduction to causal inference, Paul Rosenbaum explains key concepts and methods through real-world examples.
Format:Mode of access: Internet via World Wide Web.
ISBN:9780674982697
9783110543315
DOI:10.4159/9780674982697
Access:restricted access
Hierarchical level:Monograph
Statement of Responsibility: Paul R. Rosenbaum.