Observation and Experiment : : An Introduction to Causal Inference /

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
VerfasserIn:
Rosenbaum, Paul R.,
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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245 1 0 |a Observation and Experiment :  |b An Introduction to Causal Inference /  |c Paul R. Rosenbaum. 
264 1 |a Cambridge, MA :   |b Harvard University Press,   |c [2018] 
264 4 |c ©2017 
300 |a 1 online resource (400 p.) :  |b 13 graphs, 28 tables 
336 |a text  |b txt  |2 rdacontent 
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505 0 0 |t Frontmatter --   |t Contents --   |t Preface --   |t Reading Options --   |t List of Examples --   |t Part I. Randomized Experiments --   |t 1. A Randomized Trial --   |t 2. Structure --   |t 3. Causal Inference in Randomized Experiments --   |t 4. Irrationality and Polio --   |t Part II. Observational Studies --   |t 5. Between Observational Studies and Experiments --   |t 6. Natural Experiments --   |t 7. Elaborate Theories --   |t 8. Quasi-experimental Devices --   |t 9. Sensitivity to Bias --   |t 10. Design Sensitivity --   |t 11. Matching Techniques --   |t 12. Biases from General Dispositions --   |t 13. Instruments --   |t 14. Conclusion --   |t Appendix: Bibliographic Remarks --   |t Notes --   |t Glossary: Notation and Technical Terms --   |t Suggestions for Further Reading --   |t Acknowledgments --   |t Index 
506 0 |a restricted access  |u http://purl.org/coar/access_right/c_16ec  |f online access with authorization  |2 star 
520 |a 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. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 24. Aug 2021) 
650 0 |a Inference. 
650 0 |a Observation (Scientific method). 
650 0 |a Probabilities. 
650 0 |a Science  |x Experiments. 
650 7 |a MATHEMATICS / Probability & Statistics / General.  |2 bisacsh 
773 0 8 |i Title is part of eBook package:  |d De Gruyter  |t Harvard University Press Complete eBook-Package 2017  |z 9783110543315 
856 4 0 |u https://doi.org/10.4159/9780674982697 
856 4 0 |u https://www.degruyter.com/isbn/9780674982697 
856 4 2 |3 Cover  |u https://www.degruyter.com/cover/covers/9780674982697.jpg 
912 |a 978-3-11-054331-5 Harvard University Press Complete eBook-Package 2017  |b 2017 
912 |a GBV-deGruyter-alles 

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