Multiple imputation of missing data in a dataset using MICT or MICT-timing methods. The core idea of the algorithms is to fill gaps of missing data, which is the typical form of missing data in a longitudinal setting, recursively from their edges. Prediction is based on either a multinomial or random forest regression model. Covariates and time-dependent covariates can be included in the model.
Version: | 2.2.0 |
Depends: | R (≥ 3.5.0) |
Imports: | Amelia, cluster, dfidx, doRNG, doSNOW, dplyr, foreach, graphics, mlr, nnet, parallel, plyr, ranger, rms, stats, stringr, TraMineR, TraMineRextras, utils, mice, parallelly |
Suggests: | R.rsp, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2025-01-15 |
DOI: | 10.32614/CRAN.package.seqimpute |
Author: | Kevin Emery [aut, cre], Anthony Guinchard [aut], Andre Berchtold [aut], Kamyar Taher [aut] |
Maintainer: | Kevin Emery <kevin.emery at unige.ch> |
BugReports: | https://github.com/emerykevin/seqimpute/issues |
License: | GPL-2 |
URL: | https://github.com/emerykevin/seqimpute |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | seqimpute results |
Reference manual: | seqimpute.pdf |
Vignettes: |
seqimpute vignette (source) |
Package source: | seqimpute_2.2.0.tar.gz |
Windows binaries: | r-devel: seqimpute_2.2.0.zip, r-release: seqimpute_2.2.0.zip, r-oldrel: seqimpute_2.2.0.zip |
macOS binaries: | r-devel (arm64): seqimpute_2.2.0.tgz, r-release (arm64): seqimpute_2.2.0.tgz, r-oldrel (arm64): seqimpute_2.2.0.tgz, r-devel (x86_64): seqimpute_2.2.0.tgz, r-release (x86_64): seqimpute_2.2.0.tgz, r-oldrel (x86_64): seqimpute_2.2.0.tgz |
Old sources: | seqimpute archive |
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