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

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

The field of missing data in statistics has been extensively studied in recent years. This revised Third Edition is an updated and comprehensive approach to solving missing data problems. Written by renowned experts Donald Rubin and Roderick Little, this textbook blends practical application and theory using a methodology that effectively handles missing data. The authors present historical approaches to missing data problems and then provide straightforward multivariate analysis methods for missing data. They deliver a coherent statistical model-based theory to analyze missing data problems. With this theory, they offer solutions for a wide range of critical missing data problems.
Statistical Analysis with Missing Data, 3rd Edition, (PDF) begins by introducing readers to the subject matter and the different approaches to solving it. The authors study the mechanisms and patterns that create missing data, provide a taxonomy of missing data, and then analyze missing data in experiments. They also delve into complete-case, available-case, and weighting methods for analyzing data. This new edition includes expanded coverage on new topics such as nonresponse in sample surveys, diagnostic methods, causal inference, sensitivity analysis and more.
Here is what you can find in this book:

  • An expanded bibliography for a more complete study of the topic
  • Over 150 exercises (including many new ones) to practice your skills
  • Fully revised and written by renowned experts on the subject
  • Extensive coverage of recent methods, such as Bayesian methods, robust alternatives to weighting, and multiple imputation

In 2017, the authors were awarded The Karl Pearson Prize by the International Statistical Institute for their significant research contribution and influence on methodology, statistical theory, or applications. Their work was defined as transforming and has attracted widespread attention and praise. This book is perfect for upper-undergraduate and/or beginning graduate-level students and is an excellent resource for practitioners and statisticians in government and industry.
PLEASE NOTE: This product only includes the downloadable eBook version of Statistical Analysis with Missing Data, 3rd Edition in PDF format. No access codes are provided.
You won’t regret incorporating this book into your study materials for statistical analysis with missing data problems.

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