Statistical Analysis with Missing Data Book [PDF] Download

Download the fantastic book titled Statistical Analysis with Missing Data written by Roderick J. A. Little, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Statistical Analysis with Missing Data", which was released on 23 April 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Mathematics genre.

Summary of Statistical Analysis with Missing Data by Roderick J. A. Little PDF

An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated “classic” written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute, for a research contribution that has had profound influence on statistical theory, methodology or applications. Their work "has been no less than defining and transforming." (ISI) Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry.


Detail About Statistical Analysis with Missing Data PDF

  • Author : Roderick J. A. Little
  • Publisher : John Wiley & Sons
  • Genre : Mathematics
  • Total Pages : 462 pages
  • ISBN : 0470526793
  • PDF File Size : 9,8 Mb
  • Language : English
  • Rating : 5/5 from 1 reviews

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Statistical Analysis with Missing Data

Statistical Analysis with Missing Data
  • Publisher : John Wiley & Sons
  • File Size : 36,9 Mb
  • Release Date : 23 April 2019
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An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two

Statistical Analysis with Missing Data

Statistical Analysis with Missing Data
  • Publisher : John Wiley & Sons
  • File Size : 38,6 Mb
  • Release Date : 21 March 2019
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An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two

Statistical Power Analysis with Missing Data

Statistical Power Analysis with Missing Data
  • Publisher : Routledge
  • File Size : 35,8 Mb
  • Release Date : 20 August 2009
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Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This

Statistical Analysis with Missing Data

Statistical Analysis with Missing Data
  • Publisher : John Wiley & Sons
  • File Size : 50,6 Mb
  • Release Date : 25 August 2014
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* Emphasizes the latest trends in the field. * Includes a new chapter on evolving methods. * Provides updated or revised material in most of the chapters.

Statistical Analysis With Missing Data

Statistical Analysis With Missing Data
  • Publisher : Unknown Publisher
  • File Size : 51,8 Mb
  • Release Date : 11 May 1987
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Blending theory and application, this study reviews historical approaches to the subject and provides rigorous yet simple methods for multivariate analysis with missing values.

Missing Data

Missing Data
  • Publisher : Springer Science & Business Media
  • File Size : 29,8 Mb
  • Release Date : 08 June 2012
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Missing data have long plagued those conducting applied research in the social, behavioral, and health sciences. Good missing data analysis solutions are available, but practical information about implementation of these

Handbook of Missing Data Methodology

Handbook of Missing Data Methodology
  • Publisher : CRC Press
  • File Size : 35,5 Mb
  • Release Date : 06 November 2014
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Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing

Flexible Imputation of Missing Data, Second Edition

Flexible Imputation of Missing Data, Second Edition
  • Publisher : CRC Press
  • File Size : 51,8 Mb
  • Release Date : 17 July 2018
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Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple

Missing Data

Missing Data
  • Publisher : SAGE Publications
  • File Size : 23,9 Mb
  • Release Date : 08 May 2024
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Sooner or later anyone who does statistical analysis runs into problems with missing data in which information for some variables is missing for some cases. Why is this a problem?

The Prevention and Treatment of Missing Data in Clinical Trials

The Prevention and Treatment of Missing Data in Clinical Trials
  • Publisher : National Academies Press
  • File Size : 28,6 Mb
  • Release Date : 21 December 2010
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Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known