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• LDR

  00000cam c2200205 c 4500

• 001

  000000525296

• 005

  20181108214349

• 008

  180719s2013 us b 101 0 eng

• 010

  ▼a  2013010114

• 020

  ▼a  9781439849637 (hardback : acid-free paper)

• 035

  ▼a  (KERIS)BIB000013258727

• 040

  ▼a  211047
  ▼c  211047
  ▼d  211047

• 082

  ▼a  519.5/4
  ▼2  23

• 100

  ▼a  Kim, Jae Kwang,
  ▼d  1968-

• 245

  ▼a  Statistical methods for handling incomplete data/
  ▼d  Jae Kwang Kim ,
  ▼e  Jun Shao.

• 260

  ▼a  Boca Raton:
  ▼b  CRC Press,
  ▼c  2013.

• 300

  ▼a  xi, 211 p.;
  ▼c  25 cm.

• 504

  ▼a  Includes bibliographical references and index.

• 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"--Provided by publisher.

• 650

  ▼a  Missing observations (Statistics)

• 650

  ▼a  Multiple imputation (Statistics)

• 650

  ▼a  MATHEMATICS / Probability & Statistics / General.
  ▼2  bisacsh

• 700

  ▼a  Shao, Jun,
  ▼c  (Statistician)

• 990

  ▼a  김자옥
  ▼b  김자옥

• 991

  ▼a  단행본

• 090

  ▼a  519.5
  ▼b  K56s