Applied Bayesian Modeling and Causal Inference from Incomplete-Data PerspectivesISBN: 978-0-470-09043-5
Hardcover
440 pages
September 2004
This is a Print-on-Demand title. It will be printed specifically to fill your order. Please allow an additional 10-15 days delivery time. The book is not returnable.
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This book brings together a collection of articles on
statistical methods relating to missing data analysis, including
multiple imputation, propensity scores, instrumental variables, and
Bayesian inference. Covering new research topics
and real-world examples which do not feature in many
standard texts. The book is dedicated to Professor Don Rubin
(Harvard). Don Rubin has made fundamental contributions to
the study of missing data.
Key features of the book include:
- Comprehensive coverage of an imporant area for both research and applications.
- Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques.
- Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference.
- Includes a number of applications from the social and health sciences.
- Edited and authored by highly respected researchers in the area.