Flexible Imputation of Missing Data: Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics)

Flexible Imputation of Missing Data, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics)

by Stef van Buuren

5 out of 5

Language	:	English
File size	:	58570 KB
Screen Reader	:	Supported
Print length	:	444 pages
Paperback	:	136 pages
Item Weight	:	6.1 ounces
Dimensions	:	8.27 x 0.31 x 5.83 inches

FREE

Missing data is a common problem in data analysis. It can occur for a variety of reasons, such as when respondents refuse to answer questions, when data is lost during collection or processing, or when data is simply not available.

Missing data can bias the results of data analysis, and it can make it difficult to draw valid s. Therefore, it is important to impute missing data before conducting data analysis.

There are a variety of methods for imputing missing data. The most common method is to use a single imputation method, such as mean imputation or median imputation. However, single imputation methods can bias the results of data analysis, and they can also make it difficult to assess the uncertainty of the imputed values.

Multiple imputation is a more flexible method for imputing missing data. Multiple imputation involves imputing the missing data multiple times, using different imputation models. This produces multiple complete datasets, which can be used to conduct data analysis. Multiple imputation can reduce bias and uncertainty, and it can also provide a more accurate representation of the missing data.

Overview of Flexible Imputation of Missing Data

Flexible Imputation of Missing Data: Second Edition provides a comprehensive overview of flexible statistical methods for imputing missing data. The book covers a wide range of topics, including:

• The different types of missing data
• The mechanisms that cause missing data
• The different methods for imputing missing data
• The advantages and disadvantages of different imputation methods
• The best practices for imputing missing data

The book is written in a clear and concise style, and it is packed with examples and case studies. It is an essential resource for anyone who works with missing data.

Applications of Flexible Imputation of Missing Data

Flexible Imputation of Missing Data can be used in a wide variety of applications, including:

• Imputing missing data in clinical trials
• Imputing missing data in surveys
• Imputing missing data in observational studies
• Imputing missing data in longitudinal studies
• Imputing missing data in multilevel models

The book provides detailed guidance on how to impute missing data in each of these applications.

Flexible Imputation of Missing Data: Second Edition is an essential resource for anyone who works with missing data. The book provides a comprehensive overview of flexible statistical methods for imputing missing data, and it covers a wide range of applications.

The book is written in a clear and concise style, and it is packed with examples and case studies. It is an essential resource for anyone who wants to learn more about missing data imputation.

Flexible Imputation of Missing Data, Second Edition (Chapman & Hall/CRC Interdisciplinary Statistics)

by Stef van Buuren

5 out of 5

Language	:	English
File size	:	58570 KB
Screen Reader	:	Supported
Print length	:	444 pages
Paperback	:	136 pages
Item Weight	:	6.1 ounces
Dimensions	:	8.27 x 0.31 x 5.83 inches

FREE