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Flexible Imputation of Missing Data, Paperback by van Buuren, Stef, Like New ...

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Item specifics

Condition
Like New: A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is ...
Book Title
Flexible Imputation of Missing Data
ISBN
9781032178639

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1032178639
ISBN-13
9781032178639
eBay Product ID (ePID)
22078394286

Product Key Features

Number of Pages
444 Pages
Language
English
Publication Name
Flexible Imputation of Missing Data, Second Edition
Publication Year
2021
Subject
Probability & Statistics / General, General
Type
Textbook
Subject Area
Mathematics
Author
Stef Van Buuren
Series
Chapman and Hall/Crc Interdisciplinary Statistics Ser.
Format
Trade Paperback

Dimensions

Item Weight
16.3 Oz
Item Length
9.2 in
Item Width
6.1 in

Additional Product Features

Edition Number
2
Intended Audience
College Audience
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
519.535
Table Of Content
1. Introduction 2. Multiple imputation 3. Univariate missing data 4. Multivariate missing data 5. Analysis of imputed data 6. Imputation in practice 7. Multilevel multiple imputation 8. Individual Causal Effects 9. Measurement issues 10. Selection issues 11. Longitudinal data 12. Conclusion
Synopsis
This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field., 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 imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader's intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.
LC Classification Number
QA278

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