Observation and Experiment: An Introduction to Causal Inference

Observation and Experiment: An Introduction to Causal Inference

by Paul Rosenbaum
Observation and Experiment: An Introduction to Causal Inference

Observation and Experiment: An Introduction to Causal Inference

by Paul Rosenbaum

eBook

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Overview

A daily glass of wine prolongs life—yet alcohol can cause life-threatening cancer. Some say raising the minimum wage will decrease inequality while others say it increases unemployment. Scientists once confidently claimed that hormone replacement therapy reduced the risk of heart disease but now they equally confidently claim it raises that risk. What should we make of this endless barrage of conflicting claims?

Observation and Experiment is an introduction to causal inference by one of the field’s leading scholars. An award-winning professor at Wharton, Paul Rosenbaum explains key concepts and methods through lively examples that make abstract principles accessible. He draws his examples from clinical medicine, economics, public health, epidemiology, clinical psychology, and psychiatry to explain how randomized control trials are conceived and designed, how they differ from observational studies, and what techniques are available to mitigate their bias.

“Carefully and precisely written…reflecting superb statistical understanding, all communicated with the skill of a master teacher.”
—Stephen M. Stigler, author of The Seven Pillars of Statistical Wisdom

“An excellent introduction…Well-written and thoughtful…from one of causal inference’s noted experts.”
Journal of the American Statistical Association

“Rosenbaum is a gifted expositor…an outstanding introduction to the topic for anyone who is interested in understanding the basic ideas and approaches to causal inference.”
Psychometrika

“A very valuable contribution…Highly recommended.”
International Statistical Review


Product Details

ISBN-13: 9780674983243
Publisher: Harvard University Press
Publication date: 08/14/2017
Sold by: Barnes & Noble
Format: eBook
Pages: 400
File size: 4 MB

About the Author

Paul R. Rosenbaum is Robert G. Putzel Professor of Statistics at the Wharton School and a Senior Fellow of the Leonard Davis Institute of Health Economics, University of Pennsylvania.

Table of Contents

Cover 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
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