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CRAN: Package missr

missr: Classify Missing Data as MCAR, MAR, or MNAR

Classify missing data as missing completely at random (MCAR), missing at random (MAR), or missing not at random (MNAR). This step is required before handling missing data (e.g. mean imputation) so that bias is not introduced. See Little (1988) <doi:10.1080/01621459.1988.10478722> for the statistical rationale for the methods used.

Version: 1.0.1
Depends: R (≥ 3.5)
Imports: norm, tibble, lifecycle
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-06-04
DOI: 10.32614/CRAN.package.missr
Author: Noah William Trelawny Hellen [aut, cre, cph]
Maintainer: Noah William Trelawny Hellen <noahhellen at gmail.com>
BugReports: https://github.com/NoahHellen/missr/issues
License: MIT + file LICENSE
URL: https://github.com/NoahHellen/missr, https://noahhellen.github.io/missr/
NeedsCompilation: no
Language: en-GB
Materials: README, NEWS
CRAN checks: missr results

Documentation:

Reference manual: missr.html , missr.pdf
Vignettes: background (source)
introduction (source)

Downloads:

Package source: missr_1.0.1.tar.gz
Windows binaries: r-devel: missr_1.0.1.zip, r-release: missr_1.0.1.zip, r-oldrel: missr_1.0.1.zip
macOS binaries: r-release (arm64): missr_1.0.1.tgz, r-oldrel (arm64): missr_1.0.1.tgz, r-release (x86_64): missr_1.0.1.tgz, r-oldrel (x86_64): missr_1.0.1.tgz
Old sources: missr archive

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