Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives An Essential Journey With Donald Rubin's Statistical Family - Wiley Series in Probability and Statistics

Hardback (23 Jul 2004)

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Publisher's 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.

Book information

ISBN: 9780470090435
Publisher: Wiley
Imprint: John Wiley & Sons, Inc.
Pub date:
DEWEY: 519.542
DEWEY edition: 22
Language: English
Number of pages: 407
Weight: 734g
Height: 162mm
Width: 321mm
Spine width: 29mm