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 te...
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Group Author: | ; ; |
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Published: |
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Literature type: | eBook |
Language: | English |
Series: |
Wiley series in probability and statistics |
Subjects: | |
Online Access: |
http://onlinelibrary.wiley.com/book/10.1002/0470090456 |
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. Covering new research topics and real-world examples which do not feature in many standard texts. |
Carrier Form: | 1 online resource (xix, 407 pages) : illustrations. |
Bibliography: | Includes bibliographical references (pages 361-400) and index. |
ISBN: |
0470090448 9780470090442 047009043X 9780470090435 0470090456 9780470090459 |
Index Number: | QA279 |
CLC: | O212.8 |
Contents: | Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives; Contents; Preface; I Casual inference and observational studies; II Missing data modeling; III Statistical modeling and computation; IV Applied Bayesian inference; References; Index. |