Observation and Experiment: An Introduction to Causal Inference - Hardcover

Rosenbaum, Paul

Hardcover

ISBN 10: 067497557X ISBN 13: 9780674975576

Publisher: Harvard University Press, 2017

Synopsis

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.

About this title

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.

From the Back Cover

In this timely book Paul Rosenbaum lets you in on a secret: the most important ideas in statistics can be clearly explained in plain English, with little or no math. Rosenbaum takes a layered approach to teaching causal analysis, first explaining the intuition behind the most important estimators in use today, and then providing a minimal amount of mathematics to further explain the concepts.The exposition is vividly illustrated throughout with important applications of statistics to key questions of causality in public health, economics, political science, psychology, and many other fields.

Alan B. Krueger, Princeton University

Paul Rosenbaum's clear explanations, applied examples, and intuitive descriptions of methods such as randomized trials, propensity scores, matching and instrumental variables make this an excellent introduction to causal inference for a broad range of readers, including those with no technical background.

Elizabeth A. Stuart, Johns Hopkins Bloomberg School of Public Health

His earlier writings having captivated a generation of causal inference methodologists, Rosenbaum has now written an authoritative and largely non-technical book explaining causal inference in the social and medical sciences. Combining artful explanations with vivid examples from a range of discipline, Observation and Experiment creates a clearly signed path through causality's shifting sands.
Ben Hansen, University of Michigan

Edition details

• Publisher: Harvard University Press
• Publication date: 2017
• Language: English
• ISBN 10: 067497557X
• ISBN 13: 9780674975576
• Binding: Hardcover
• Number of pages: 400