"Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives" - Information and Links:

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives - Info and Reading Options

an essential journey with Donald Rubin's statistical family

Book's cover
The cover of “Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives” - Open Library.
Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives - cover - The Open Library
Book's cover - The Open Library
Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives - cover - Google Books
Book's cover - Google Books

"Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives" was published by Wiley in 2004 - Chichester, West Sussex, England, the book is classified in Mathematics genre, it has 407 pages and the language of the book is English.


“Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives” Metadata:

  • Title: ➤  Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
  • Author:
  • Language: English
  • Number of Pages: 407
  • Is Family Friendly: Yes - No Mature Content
  • Publisher: Wiley
  • Publish Date:
  • Publish Location: ➤  Chichester, West Sussex, England
  • Genres: Mathematics

“Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives” Subjects and Themes:

Edition Specifications:

  • Pagination: xix, 407 p. :

Edition Identifiers:

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Snippets and Summary:

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.

"Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives" Description:

Google Books:

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.

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  • Public Domain: No
  • Availability Status: Partially available
  • Availability Status for country: US.
  • Available Formats: Text is not avialbe, image copy is available.
  • Google Books Link: Google Books

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