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Flexible Imputation of Missing Data, Second Edition

Stef van Buuren
€56.99
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A01=Stef van Buuren
advanced missing data strategies
Analysis of imputed data
Author_Stef van Buuren
Average Causal Effect
BMI SDS
Category=PBT
Category=PS
causal inference
causal inference techniques
Complete Case Analysis
Complete Data Models
data analysis methods
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eq_nobargain
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Fcs
Height SDS
Ice
Imputation Model
Imputed Data
Imputed Datasets
incomplete data
Listwise Deletion
Longitudinal data
longitudinal studies
MAR Assumption
Measurement issues
MICE
Missing Data
Missing Data Mechanism
Missing Data Pattern
Missing Data Rate
Missing Values
multilevel modelling
Multiple Imputation
Multiply Imputed Data
Multivariate missing data
nonignorable
Pattern Mixture Model
quantitative research
R software
Random Intercepts
Random Slopes
Regression Imputation
statistical inference
Stochastic Regression Imputation
Worm Plot

Product details

  • ISBN 9781032178639
  • Weight: 460g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Sep 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

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.

About Stef van Buuren

Stef van Buuren is a statistical consultant at the Netherlands Organisation for Applied Scientific Research TNO in Leiden with a broad knowledge of quantitative issues in public health. Since 2015, Van Buuren holds is the world's first Professor of Missing Data at the department of Methodology & Statistics, FSS, University of Utrecht. He is the originator of various new statistical tools.

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