CALIBERrfimpute: Multiple Imputation Using MICE and Random Forest

Functions to impute using random forest under full conditional specifications (multivariate imputation by chained equations). The methods are described in Shah and others (2014) <doi:10.1093/aje/kwt312>.

Version: 1.0-7
Depends: mice (≥ 2.20)
Imports: mvtnorm, randomForest
Suggests: missForest, rpart, survival, xtable, ranger
Published: 2022-12-04
DOI: 10.32614/CRAN.package.CALIBERrfimpute
Author: Anoop Shah [aut, cre], Jonathan Bartlett [ctb], Harry Hemingway [ths], Owen Nicholas [ths], Aroon Hingorani [ths]
Maintainer: Anoop Shah <anoop at doctors.org.uk>
License: GPL-3
NeedsCompilation: no
Citation: CALIBERrfimpute citation info
Materials: NEWS
In views: MissingData
CRAN checks: CALIBERrfimpute results

Documentation:

Reference manual: CALIBERrfimpute.pdf
Vignettes: Comparison of parametric and Random Forest MICE in imputation of missing data in survival analysis

Downloads:

Package source: CALIBERrfimpute_1.0-7.tar.gz
Windows binaries: r-devel: CALIBERrfimpute_1.0-7.zip, r-release: CALIBERrfimpute_1.0-7.zip, r-oldrel: CALIBERrfimpute_1.0-7.zip
macOS binaries: r-release (arm64): CALIBERrfimpute_1.0-7.tgz, r-oldrel (arm64): CALIBERrfimpute_1.0-7.tgz, r-release (x86_64): CALIBERrfimpute_1.0-7.tgz, r-oldrel (x86_64): CALIBERrfimpute_1.0-7.tgz
Old sources: CALIBERrfimpute archive

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