Observation and Experiment: An Introduction to Causal Inference

by Paul Rosenbaum

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:	9780674241633
Publisher:	Harvard University Press
Publication date:	08/13/2019
Edition description:	Reprint
Pages:	400
Sales rank:	600,643
Product dimensions:	6.00(w) x 9.20(h) x 1.10(d)

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

Preface vii

Reading Options xi

List of Examples xv

Part I Randomized Experiments

1 A Randomized Trial 3

2 Structure 16

3 Causal Inference in Randomized Experiments 30

4 Irrationality and Polio 53

Part II Observational Studies

5 Between Observational Studies and Experiments 65

6 Natural Experiments 100

7 Elaborate Theories 118

8 Quasi-experimental Devices 142

9 Sensitivity to Bias 170

10 Design Sensitivity 194

11 Matching Techniques 212

12 Biases from General Dispositions 234

13 Instruments 258

14 Conclusion 279

Appendix: Bibliographic Remarks 283

Notes 285

Glossary: Notation and Technical Terms 345

Suggestions for Further Reading 353

Acknowledgments 355

Index 357

Editorial Reviews

The book is a very valuable contribution… Highly recommended.

International Statistical Review - Carol Joyce Blumberg

A researcher seeking instruction in the sophisticated use of [statistical significance] techniques may want to consult Observation and Experiment.

James Ryerson

A well-written and thoughtful reflection on the doing of causal inference from one of causal inference’s noted experts.

Journal of the American Statistical Association - Jameson A. Quinn and Luke W. Miratrix

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

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.

MAA Reviews - William J. Satzer

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.

Observational Studies - Dylan S. Small

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.

Psychometrika - Joel B. Greenhouse and Edward H. Kennedy