Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives

Language: English

Published by John Wiley and Sons Inc, US, 2004

047009043X / 9780470090435

Series: Book 213 of 358 - Wiley Series in Probability and Statistics

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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.

Seller Inventory # LU-9780470090435

Title
Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
Author
Andrew Gelman
Publisher
John Wiley and Sons Inc, US
Publication year
2004
Condition
New
Binding
Hardback
Language
English
ISBN 10
047009043X
ISBN 13
9780470090435
Item weight
794 grams
Series
Book 213 of 358: Wiley Series in Probability and Statistics

Rarewaves.com UK

London, United Kingdom

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