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Statistical Analysis with Missing Data
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Statistical Analysis with Missing Data

Statistical Analysis with Missing Data

Roderick J. A. / Rubin Little

464 pages, parution le 11/07/2019

Résumé

Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values. The authors, renowned gurus on the subject, provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism and apply the theory to a wide range of important missing data problems.

Roderick J. A. Little, PhD., is Richard D. Remington Distinguished University Professor of Biostatistics, Professor of Statistics, and Research Professor, Institute for Social Research, at the University of Michigan.

Donald B. Rubin, PhD., is Professor, Yau Mathematical Sciences Center, Tsinghua University; Murray Shusterman Senior Research Fellow, Department of Statistical Science, Fox School of Business at Temple University; and Professor Emeritus, Harvard University.

Caractéristiques techniques

  PAPIER
Éditeur(s) Wiley
Auteur(s) Roderick J. A. / Rubin Little
Parution 11/07/2019
Nb. de pages 464
EAN13 9780470526798

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