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Flexible Imputation of Missing Data

A hands-on approach to multiple imputation

A new book on MICE

Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science —multiple imputation— fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which are missing data problems in disguise.

Flexible Imputation of Missing Data is supported by many examples using real data. It provides detailed guidance of implementation in R throughout the book. The tables below contains the R code used in the book, as well as the output and graphs it produces using mice 2.12.

Flexible Imputation of Missing Data - Online materials
Chapter R code Output Graphs
1 fimd1.r fimd1.log fimd1.pdf
2 fimd2.r fimd2.log fimd2.pdf
3 fimd3.r fimd3.log fimd3.pdf
4 fimd4.r fimd4.log fimd4.pdf
5 fimd5.r fimd5.log fimd5.pdf
6 fimd6.r fimd6.log  
7 fimd7.r fimd7.log fimd7.pdf
8 fimd8.r fimd8.log fimd8.pdf
9 fimd9.r fimd9.log fimd9.pdf

In the mice 2.12 package, the files fimd1.r-fimd9.r are located in the 'doc' subdirectory.

Flexible Imputation of Missing Data - Datasets used
Dataset Where available?
airquality package datasets
boys package mice
db package gamlss
fdd package mice
fdgs package mice
leiden85 sorry, not yet available
nhanes package mice
nhanes2 package mice
mammalsleep package mice
pattern4 package mice
fdd package mice
pops sorry, not yet available
potthoffroy package mice
selfreport package mice
sleep package mice, as mammalsleep
tbc package mice, subset
walking package mice
whiteside package MASS

Biobligraphic information: Van Buuren, S. (2012), Flexible Imputation of Missing Data. Chapman & Hall/CRC, Boca Raton, FL. ISBN 9781439868249. CRC Press, Amazon

Electronic copy in Utrecht library (credentials required)

FIMD