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Statistical methods for handling inc...

Kim, Jae Kwang, (1968-.)

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Statistical methods for handling incomplete data /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Statistical methods for handling incomplete data // Jae Kwang Kim, Jun Shao.
作者:	Kim, Jae Kwang,
其他作者:	Shao, Jun
出版者:	Boca Raton, FL :CRC Press, : 2014.,
面頁冊數:	xi, 211 p. :ill. ;25 cm.
標題:	Missing observations (Statistics). -
ISBN:	9781439849637

Statistical methods for handling incomplete data /
Kim, Jae Kwang,1968-.

Statistical methods for handling incomplete data /Jae Kwang Kim, Jun Shao. - Boca Raton, FL :CRC Press,2014. - xi, 211 p. :ill. ;25 cm. - A Chapman & Hall book..

Includes bibliographical references and index

Likelihood-based approach --

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 application, and statistical matching. The book is suitable for use as a textbook for a graduate course in statistics departments or as a reference book for those interested in this area. Some of the research ideas introduced in the book can be developed further for specific applications.

ISBN: 9781439849637GBP59.99

LCCN: 2013010114Subjects--Topical Terms:

753104
Missing observations (Statistics).

LC Class. No.: QA276.8 / .K55 2014

Dewey Class. No.: 519.5/4

Statistical methods for handling incomplete data /
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100 1 $a Kim, Jae Kwang, $d 1968-. $3 2121461
245 1 0 $a Statistical methods for handling incomplete data / $c Jae Kwang Kim, Jun Shao.
260 # $a Boca Raton, FL : $b CRC Press, $c 2014.
300 $a xi, 211 p. : $b ill. ; $c 25 cm.
490 1 0 $a A Chapman & Hall book.
504 $a Includes bibliographical references and index $t .
505 0 # $t Likelihood-based approach -- $t Computation -- $t Imputation -- $t Propensity scoring approach -- $t Nonignorable missing data -- $t Longitudinal and clustered data -- $t Application to survey sampling -- $t Statistical matching.
520 # $a 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 application, and statistical matching. The book is suitable for use as a textbook for a graduate course in statistics departments or as a reference book for those interested in this area. Some of the research ideas introduced in the book can be developed further for specific applications.
650 # 0 $a Missing observations (Statistics). $3 753104
650 # 0 $a Multiple imputation (Statistics). $3 2121463
700 1 # $a Shao, Jun $c (Statistician). $3 2121462