Causal Inference
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Causal Inference
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Causal Inference by Paul R Rosenbaum
A nontechnical guide to the basic ideas of modern causal inference, with illustrations from health, the economy, and public policy. Which of two antiviral drugs does the most to save people infected with Ebola virus? Does a daily glass of wine prolong or shorten life? Does winning the lottery make you more or less likely to go bankrupt? How do you identify genes that cause disease? Do unions raise wages? Do some antibiotics have lethal side effects? Does the Earned Income Tax Credit help people enter the workforce? Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. Ideas are illustrated with examples from medicine, epidemiology, economics and business, the social sciences, and public policy.Paul R. Rosenbaum is the Robert G. Putzel Professor of Statistics at the Wharton School of the University of Pennsylvania. He is a fellow of the American Statistical Association. In 2019, he received the R. A. Fisher Award, and in 2003 the George W. Snedecor Award, both from the Committee of Presidents of Statistical Societies (COPSS). He is the author of Observation and Experiment: An Introduction to Causal Inference (2017) and Observational Studies, 2nd edition (Springer 2002).
| SKU | Unavailable |
| ISBN 13 | 9780262545198 |
| ISBN 10 | 0262545195 |
| Title | Causal Inference |
| Author | Paul R Rosenbaum |
| Series | The Mit Press Essential Knowledge Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | MIT Press Ltd |
| Year published | 2023-04-04 |
| Number of pages | 232 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |