missMethods: Methods for Missing Data

Supply functions for the creation and handling of missing data as well as tools to evaluate missing data methods. Nearly all possibilities of generating missing data discussed by Santos et al. (2019) <doi:10.1109/ACCESS.2019.2891360> and some additional are implemented. Functions are supplied to compare parameter estimates and imputed values to true values to evaluate missing data methods. Evaluations of these types are done, for example, by Cetin-Berber et al. (2019) <doi:10.1177/0013164418805532> and Kim et al. (2005) <doi:10.1093/bioinformatics/bth499>.

Version: 0.4.0
Imports: mvtnorm, stats, utils
Suggests: ggplot2, knitr, lpSolve, norm, rmarkdown, testthat (≥ 2.1.0), tibble
Published: 2022-09-16
DOI: 10.32614/CRAN.package.missMethods
Author: Tobias Rockel [aut, cre]
Maintainer: Tobias Rockel <Rockel.To at gmail.com>
BugReports: https://github.com/torockel/missMethods/issues
License: GPL-3
URL: https://github.com/torockel/missMethods
NeedsCompilation: no
Materials: README NEWS
In views: MissingData
CRAN checks: missMethods results


Reference manual: missMethods.pdf
Vignettes: Generating-missing-values


Package source: missMethods_0.4.0.tar.gz
Windows binaries: r-devel: missMethods_0.4.0.zip, r-release: missMethods_0.4.0.zip, r-oldrel: missMethods_0.4.0.zip
macOS binaries: r-release (arm64): missMethods_0.4.0.tgz, r-oldrel (arm64): missMethods_0.4.0.tgz, r-release (x86_64): missMethods_0.4.0.tgz, r-oldrel (x86_64): missMethods_0.4.0.tgz
Old sources: missMethods archive

Reverse dependencies:

Reverse imports: Indicator, kssa, MCARtest, QoLMiss
Reverse suggests: imputeGeneric


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