Name: Flexible Imputation of Missing Data, Second Edition (Chapman & Hall (en Inglés)
SKU: 51232901
Price: 145.87 USD
Availability: InStock
Author: Stef Van Buuren

portada Flexible Imputation of Missing Data, Second Edition (Chapman & Hall (en Inglés)

Flexible Imputation of Missing Data, Second Edition (Chapman & Hall (en Inglés)

Formato

Libro Físico

Editorial

Crc Pr Inc

Autor

Stef Van Buuren

Año

2018

Idioma

Inglés

N° páginas

444

Encuadernación

Tapa Dura

Dimensiones

23.6x16.3x3.3 cm

Peso

0.84

ISBN13

9781138588318

N° edición

Categorías

Probabilidad y estadística

Flexible Imputation of Missing Data, Second Edition (Chapman & Hall (en Inglés)

Stef Van Buuren (Autor) · Crc Pr Inc · Tapa Dura

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Reseña del libro "Flexible Imputation of Missing Data, Second Edition (Chapman & Hall (en Inglés)"

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.