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Multiple Imputation of Missing Data in Practice

- Basic Theory and Analysis Strategies
Af: Chiu-Hsieh Hsu, Guangyu Zhang, Yulei He Engelsk Paperback

Multiple Imputation of Missing Data in Practice

- Basic Theory and Analysis Strategies
Af: Chiu-Hsieh Hsu, Guangyu Zhang, Yulei He Engelsk Paperback
Tjek vores konkurrenters priser

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis. Over the past 40 years or so, multiple imputation has gone through rapid development in both theories and applications. It is nowadays the most versatile, popular, and effective missing-data strategy that is used by researchers and practitioners across different fields. There is a strong need to better understand and learn about multiple imputation in the research and practical community.

Accessible to a broad audience, this book explains statistical concepts of missing data problems and the associated terminology. It focuses on how to address missing data problems using multiple imputation. It describes the basic theory behind multiple imputation and many commonly-used models and methods. These ideas are illustrated by examples from a wide variety of missing data problems. Real data from studies with different designs and features (e.g., cross-sectional data, longitudinal data, complex surveys, survival data, studies subject to measurement error, etc.) are used to demonstrate the methods. In order for readers not only to know how to use the methods, but understand why multiple imputation works and how to choose appropriate methods, simulation studies are used to assess the performance of the multiple imputation methods. Example datasets and sample programming code are either included in the book or available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book).

Key Features

  1. Provides an overview of statistical concepts that are useful for better understanding missing data problems and multiple imputation analysis
  2. Provides a detailed discussion on multiple imputation models and methods targeted to different types of missing data problems (e.g., univariate and multivariate missing data problems, missing data in survival analysis, longitudinal data, complex surveys, etc.)
  3. Explores measurement error problems with multiple imputation
  4. Discusses analysis strategies for multiple imputation diagnostics
  5. Discusses data production issues when the goal of multiple imputation is to release datasets for public use, as done by organizations that process and manage large-scale surveys with nonresponse problems
  6. For some examples, illustrative datasets and sample programming code from popular statistical packages (e.g., SAS, R, WinBUGS) are included in the book. For others, they are available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book)
Tjek vores konkurrenters priser
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kr 592
Fragt: 39 kr
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20 kr
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God 4 anmeldelser på
Tjek vores konkurrenters priser

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis. Over the past 40 years or so, multiple imputation has gone through rapid development in both theories and applications. It is nowadays the most versatile, popular, and effective missing-data strategy that is used by researchers and practitioners across different fields. There is a strong need to better understand and learn about multiple imputation in the research and practical community.

Accessible to a broad audience, this book explains statistical concepts of missing data problems and the associated terminology. It focuses on how to address missing data problems using multiple imputation. It describes the basic theory behind multiple imputation and many commonly-used models and methods. These ideas are illustrated by examples from a wide variety of missing data problems. Real data from studies with different designs and features (e.g., cross-sectional data, longitudinal data, complex surveys, survival data, studies subject to measurement error, etc.) are used to demonstrate the methods. In order for readers not only to know how to use the methods, but understand why multiple imputation works and how to choose appropriate methods, simulation studies are used to assess the performance of the multiple imputation methods. Example datasets and sample programming code are either included in the book or available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book).

Key Features

  1. Provides an overview of statistical concepts that are useful for better understanding missing data problems and multiple imputation analysis
  2. Provides a detailed discussion on multiple imputation models and methods targeted to different types of missing data problems (e.g., univariate and multivariate missing data problems, missing data in survival analysis, longitudinal data, complex surveys, etc.)
  3. Explores measurement error problems with multiple imputation
  4. Discusses analysis strategies for multiple imputation diagnostics
  5. Discusses data production issues when the goal of multiple imputation is to release datasets for public use, as done by organizations that process and manage large-scale surveys with nonresponse problems
  6. For some examples, illustrative datasets and sample programming code from popular statistical packages (e.g., SAS, R, WinBUGS) are included in the book. For others, they are available at a github site (https://github.com/he-zhang-hsu/multiple_imputation_book)
Produktdetaljer
Sprog: Engelsk
Sider: 476
ISBN-13: 9781032136899
Indbinding: Paperback
Udgave:
ISBN-10: 1032136898
Udg. Dato: 27 maj 2024
Længde: 31mm
Bredde: 235mm
Højde: 155mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 27 maj 2024
Forfatter(e) Chiu-Hsieh Hsu, Guangyu Zhang, Yulei He


Kategori Psykologisk teori og skoleretninger


ISBN-13 9781032136899


Sprog Engelsk


Indbinding Paperback


Sider 476


Udgave


Længde 31mm


Bredde 235mm


Højde 155mm


Udg. Dato 27 maj 2024


Oplagsdato 27 maj 2024


Forlag Taylor & Francis Ltd