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Applied Bayesian Modeling and Causal Inference from Incomplete Data Perspectives
Andrew Gelman
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Description for Applied Bayesian Modeling and Causal Inference from Incomplete Data Perspectives
Hardcover. 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. Editor(s): Gelman, Andrew; Meng, Xiao-Li. Series: Wiley Series in Probability and Statistics. Num Pages: 436 pages, Illustrations. BIC Classification: PB. Category: (P) Professional & Vocational. Dimension: 247 x 167 x 30. Weight in Grams: 786.
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.
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 ... Read more
- Includes a number of applications from the social and health sciences.
- Edited and authored by highly respected researchers in the area.
Product Details
Format
Hardback
Publication date
2004
Publisher
John Wiley and Sons Ltd United Kingdom
Number of pages
436
Condition
New
Series
Wiley Series in Probability and Statistics
Number of Pages
440
Place of Publication
New York, United States
ISBN
9780470090435
SKU
V9780470090435
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Andrew Gelman
Andrew Gelman is Professor of Statistics and Professor of Political Science at Columbia University. He has published over 150 articles in statistical theory, methods, and computation, and in applications areas including decision analysis, survey sampling, political science, public health, and policy. His other books are Bayesian Data Analysis (1995, second edition 2003) and Teaching Statistics: A Bag of Tricks (2002). ... Read more
Reviews for Applied Bayesian Modeling and Causal Inference from Incomplete Data Perspectives
"I congratulate the editors on this volume; it really is an essential and very enjoyable journey with Don Rubin's statistical family." (Biometrics, September 2006) "…contains much current important work…" (Technometrics, November 2005) "This a useful reference book on an important topic with applications to a wide range of disciplines." (CHOICE, September 2005) “With this variety ... Read more