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

Couverture rigide

ISBN 10 : 047009043X ISBN 13 : 9780470090435

Editeur : John Wiley & Sons Inc, 2004

Synopsis

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.

A propos du livre

À propos de l'auteur

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).

Détails de l'édition

• Éditeur: John Wiley & Sons Inc
• Date d'édition: 2004
• Langue: anglais
• ISBN 10: 047009043X
• ISBN 13: 9780470090435
• Reliure: Relié
• Nombre de pages: 440
• Éditeur: Gelman Andrew, Meng Xiao-Li
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible