micemd: Multiple Imputation by Chained Equations with Multilevel Data

Addons for the 'mice' package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for 'mice'.

Version: 1.10.0
Depends: R (≥ 3.5.0), mice (≥ 2.42)
Imports: Matrix, graphics, utils, stats, MASS, parallel, nlme, lme4, mvmeta (≥ 0.4.7), jomo (≥ 2.6-3), mvtnorm, digest, abind, GJRM (≥ 0.2-6.4), mgcv, mixmeta, pbivnorm
Suggests: VIM, ggplot2, data.table, broom.mixed
Published: 2023-11-17
Author: Vincent Audigier [aut, cre] (CNAM MSDMA team), Matthieu Resche-Rigon [aut] (INSERM ECSTRA team), Johanna Munoz Avila [ctb] (Julius Center Methods Group UMC, 2022)
Maintainer: Vincent Audigier <vincent.audigier at cnam.fr>
License: GPL-2 | GPL-3
NeedsCompilation: no
In views: MissingData
CRAN checks: micemd results

Documentation:

Reference manual: micemd.pdf

Downloads:

Package source: micemd_1.10.0.tar.gz
Windows binaries: r-devel: micemd_1.10.0.zip, r-release: micemd_1.10.0.zip, r-oldrel: micemd_1.10.0.zip
macOS binaries: r-release (arm64): micemd_1.10.0.tgz, r-oldrel (arm64): micemd_1.10.0.tgz, r-release (x86_64): micemd_1.10.0.tgz
Old sources: micemd archive

Reverse dependencies:

Reverse imports: clusterMI
Reverse suggests: bipd
Reverse enhances: miceadds

Linking:

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