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Statistical methods for handling incomplete data /

"With the advances in statistical computing, there has been a rapid development of techniques and applications in missing data analysis. This book aims to cover the most up-to-date statistical theories and computational methods for analyzing incomplete data through (1)vigorous treatment of stat...

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Bibliographic Details
Main Authors: Kim, Jae Kwang, 1968
Group Author: Shao, Jun Statistician
Published: CRC Press, Taylor & Francis Group,
Publisher Address: Boca Raton :
Publication Dates: [2014]
Literature type: Book
Language: English
Series: A Chapman & Hall book
Subjects:
Missing observations Statistics
Multiple imputation Statistics
Summary: "With the advances in statistical computing, there has been a rapid development of techniques and applications in missing data analysis. This book aims to cover the most up-to-date statistical theories and computational methods for analyzing incomplete data through (1)vigorous treatment of statistical theories on likelihood-based inference with missing data, (2) comprehensive treatment of computational techniques and theories on imputation, and (3) most up-to-date treatment of methodologies involving propensity score weighting, nonignorable missing, longitudinal missing, survey sampling appl
Carrier Form: xi, 211 pages ; 25 cm.
Bibliography: Includes bibliographical references (pages 201-207) and index.
ISBN: 1439849633
9781439849637 :
Index Number: QA276
CLC: O212
Call Number: O212/K492
Contents: Likelihood-based approach -- Computation -- Imputation -- Propensity scoring approach --Nonignorable missing data -- Longitudinal and clustered data -- Application to survey sampling -- Statistical matching.

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