ABOUT THIS BOOKA 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
REVIEWSThe book is a very valuable contribution… Highly recommended.
-- Carol Joyce Blumberg International Statistical Review
A well-written and thoughtful reflection on the doing of causal inference from one of causal inference’s noted experts.
-- Jameson A. Quinn and Luke W. Miratrix Journal of the American Statistical Association
The author’s voice is an important element in the book’s success. Rosenbaum is consistently clear and direct, and seems at times to be speaking directly to the reader. His excellent set of examples (twenty-five of them altogether) bring the more theoretical discussions to life.
-- William J. Satzer MAA Reviews
A treasure trove of considerations and strategies for making causal inferences from observational studies and experiments. The book is a joy to read and contains interesting material for readers at all levels of experience with causal inference.
-- Dylan S. Small Observational Studies
Rosenbaum is a gifted expositor, and as a result, this book is an outstanding introduction to the topic for anyone who is interested in understanding the basic ideas and approaches to causal inference.
-- Joel B. Greenhouse and Edward H. Kennedy Psychometrika
A researcher seeking instruction in the sophisticated use of [statistical significance] techniques may want to consult Observation and Experiment.
-- James Ryerson New York Times Book Review
Rosenbaum’s book is, as would be expected, a carefully and precisely written treatment of its subject, reflecting superb statistical understanding, all communicated with the skill of a master teacher.
-- Stephen M. Stigler, author of The Seven Pillars of Statistical Wisdom
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