Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives

Other author Gelman, Andrew Editor
Other author Meng, Xiao-Li Editor
Format Electronic
Publication InfoHoboken : John Wiley & Sons, Incorporated
Description436 p. 22.900 x 015.200 cm.
Supplemental ContentFull text available from eBooks on EBSCOhost
Subjects

SeriesWiley Series in Probability and Statistics Ser. 674
Summary Annotation 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.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.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
ISBN9780470090459
ISBN0470090456 (Online Resource) Active Record
Standard identifier# 9780470090459
Stock number00028608

Availability

Library Location Call Number Status Item Actions
Electronic Resources Access Content Online ✔ Available