Description: Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives : An Essential Journey with Donald Rubin's Statistical Family, Hardcover by Gelman, Andrew (EDT); Meng, Xiao-Li (EDT); Rubin, Donald B. (EDT), ISBN 047009043X, ISBN-13 9780470090435, Brand New, Free shipping in the US This bookbrings together acollection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics andreal-worldexampleswhich do not feature in many standard texts.Th is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of th 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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Book Title: Applied Bayesian Modeling and Causal Inference from Incomplete-Da
Number of Pages: 440 Pages
Publication Name: Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives
Language: English
Publisher: Wiley & Sons, Incorporated, John
Subject: Probability & Statistics / Bayesian Analysis
Item Height: 1.1 in
Publication Year: 2004
Type: Textbook
Item Weight: 25.4 Oz
Author: Xiao-Li MENG
Subject Area: Mathematics
Item Length: 9.2 in
Series: Wiley Series in Probability and Statistics Ser.
Item Width: 6.1 in
Format: Hardcover
