Statistical Analysis with Missing Data
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Statistical Analysis with Missing Data

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Description

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.
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Product details

  • Hardback | 464 pages
  • 167 x 238 x 28mm | 850g
  • New York, United States
  • English
  • 3rd Edition
  • 0470526793
  • 9780470526798
  • 682,979

About Roderick J. a. Little

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.
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Rating details

12 ratings
3.83 out of 5 stars
5 8% (1)
4 67% (8)
3 25% (3)
2 0% (0)
1 0% (0)
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