micemd: Multiple Imputation by Chained Equations with Multilevel Data (original) (raw)
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 |
| DOI: | 10.32614/CRAN.package.micemd |
| 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 |
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