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010 a| 2021692680;

020 a| 9781000466348q| ebook;

020 z| 9781439849637q| hardback : acid-free paper;

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049 a| EREEa| NEHH;

050 00 a| QA276.8;

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084 a| MAT0290002| bisacsh;

100 1 a| Kim, Jae Kwang,d| 1968-?| UNAUTHORIZED;

245 10 a| Statistical methods for handling incomplete datah| [electronic resource] /c| Jae Kwang Kim, Department of Statistics Iowa State University, USA, Jun Shao, Department of Statistics University of Wisconsin - Madison, USA.;

260 a| Boca Raton :b| CRC Press, Taylor and Francis Group,c| [2014];

300 a| 1 online resource (xi, 211 pages);

504 a| Includes bibliographical references (pages 201-207) and index.;

506 a| Available only to authorized users.;

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"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

588 a| Description based on print version record and CIP data provided by publisher; resource not viewed.;

650 0 a| Missing observations (Statistics)=| ^A228878;

650 0 a| Multiple imputation (Statistics)=| ^A427597;

650 7 a| MATHEMATICS / Probability & Statistics / General.2| bisacsh;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Shao, Junc| (Statistician)?| UNAUTHORIZED;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9780429321740;

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999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 6687936-3001l| MNETm| JMUSICr| Ys| Yt| MNESSBKu| 12/19/2025x| EBOOKz| JERESOURCE;

Statistical methods for handling incomplete data / Jae Kwang Kim, Department of Statistics Iowa State University, USA, Jun Shao, Department of Statistics University of Wisconsin - Madison, USA.

Author/creator	Kim, Jae Kwang, 1968-
Other author	Shao, Jun (Statistician)
Format	Electronic
Publication Info	Boca Raton : CRC Press, Taylor and Francis Group, [2014]
Description	1 online resource (xi, 211 pages)
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Missing observations (Statistics) Multiple imputation (Statistics)

Abstract	"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"-- Provided by publisher.
Bibliography note	Includes bibliographical references (pages 201-207) and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Source of description	Description based on print version record and CIP data provided by publisher; resource not viewed.
Issued in other form	Print version: Statistical methods for handling incomplete data Boca Raton : CRC Press, Taylor & Francis Group, [2014] 9781439849637 (hardback : acid-free paper)
Genre/form	Electronic books.
LCCN	2021692680
ISBN	9781000466348 ebook
ISBN	hardback : acid-free paper

Statistical methods for handling incomplete data / Jae Kwang Kim, Department of Statistics Iowa State University, USA, Jun Shao, Department of Statistics University of Wisconsin - Madison, USA.

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