Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives by Andrew Gelman

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives by Andrew Gelman

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives: An Essential Journey with Donald Rubin's Statistical Family 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.

"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 of papers, the reader is bound to find some papers interesting…” (Journal of Applied Statistics, Vol.32, No.3, April 2005)

“I strongly recommend that libraries have a copy of this book in their reference section.” (Journal of the Royal Statistical Society Series A, June 2005)

"...a very useful addition to academic libraries…" (Short Book Reviews, Vol.24, No.3, December 2004)

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).

Xiao-Li Meng, Department of Statistics, Harvard University, USA.

SKU	Unavailable
ISBN 13	9780470090435
ISBN 10	047009043X
Title	Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
Author	Andrew Gelman
Series	Wiley Series In Probability And Statistics
Condition	Unavailable
Binding Type	Hardback
Publisher	John Wiley & Sons Inc
Year published	2004-07-23
Number of pages	440
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.