In the daily news and the scientific literature, we are faced with conflicting claims about the effects caused by some treatments, behaviors, and policies. A daily glass of wine prolongs life, or so we are told. Yet we are also told that alcohol can cause life-threatening cancer and that pregnant women should abstain from drinking. Some say that raising the minimum wage decreases inequality while others say it increases unemployment. Investigators once confidently claimed that hormone replacement therapy reduces the risk of heart disease but today investigators confidently claim it raises that risk. How should we study such questions?
Observation and Experiment is an introduction to causal inference from one of the field’s leading scholars. Using minimal mathematics and statistics, Paul Rosenbaum explains key concepts and methods through scientific examples that make complex ideas concrete and abstract principles accessible.
Some causal questions can be studied in randomized trials in which coin flips assign individuals to treatments. But because randomized trials are not always practical or ethical, many causal questions are investigated in nonrandomized observational studies. To illustrate, Rosenbaum draws examples from clinical medicine, economics, public health, epidemiology, clinical psychology, and psychiatry. Readers gain an understanding of the design and interpretation of randomized trials, the ways they differ from observational studies, and the techniques used to remove, investigate, and appraise bias in observational studies. Observation and Experiment is a valuable resource for anyone with a serious interest in the empirical study of human health, behavior, and well-being.
|Edition description:||New Edition|
|Product dimensions:||6.00(w) x 9.30(h) x 1.40(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
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
Glossary: Notation and Technical Terms 345
Suggestions for Further Reading 353