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Statistical Analysis with Missing Data (3rd Edition) – eBook

eBook Details

  • Authors: Donald B. Rubin, Roderick J. A. Little
  • File Size: 8 MB
  • Format: PDF
  • Length: 463 Pages
  • Publisher: Wiley; 3rd edition
  • Publication Date: March 12, 2019
  • Language: English
  • ASIN: B07Q25CNSD
  • ISBN-10: 1118595696,  0470526793
  • ISBN-13: 9780470526798, 9781118595695, 9781118596012

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About The Author

Donald B. Rubin

Roderick J. A. Little

Revised, comprehensive treatment of a classic textbook on missing data in statistics.

The topic of missing data has got considerable attention in recent decades. This new Third Edition by two recognized experts provides an up-to-date account of a practical methodology for handling missing data problems. Blending application and theory, authors Donald Rubin and Roderick Little review historical approaches to the subject and explain simple methods for multivariate analysis with missing values. They then offer a coherent theory for analyzing problems based on likelihoods derived from statistical models for the data and the missing data mechanism. Then they implement the theory to a wide range of critical missing data problems.

Statistical Analysis with Missing Data, 3rd Edition, (PDF) starts by introducing readers to the subject and approaches toward solving it. It looks at the mechanisms and patterns that create the missing data, in addition to a taxonomy of missing data. It then analyzes missing data in experiments before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include the latest work on topics such as nonresponse in sample surveys, diagnostic methods, causal inference, and sensitivity analysis, among a host of other topics.

  • Includes an updated and expanded bibliography
  • Features more than 150 exercises (including many new ones)
  • A revised “classic” written by renowned authorities on the subject
  • Revises earlier topics based on past student feedback and class experience
  • Includes recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods

The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute for a research contribution that has had a profound influence on methodology, statistical theory, or applications. Their work “has been no less than defining and transforming.” (ISI)

Statistical Analysis with Missing Data 3e is a perfect textbook for upper-undergraduate and/or beginning graduate-level students. It is also an excellent source of information for applied practitioners and statisticians in government and industry.

NOTE: The product only includes the ebook Statistical Analysis with Missing Data 3rd Edition in PDF. No access codes are included.

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