opImputation: Optimal Selection of Imputation Methods for Pain-Related Numerical Data

A model-agnostic framework for selecting dataset-specific imputation methods for missing values in numerical data related to pain. Lotsch J, Ultsch A (2025) "A model-agnostic framework for dataset-specific selection of missing value imputation methods in pain-related numerical data" Canadian Journal of Pain (in minor revision).

Version: 0.6
Depends: R (≥ 3.5.0)
Imports: parallel, Rfit, methods, stats, caret, ABCanalysis, ggplot2, future, future.apply, progressr, missForest, utils, mice, miceRanger, multiUS, Amelia, mi, reshape2, DataVisualizations, abind, cowplot, twosamples, ggh4x, ggrepel, tools
Suggests: testthat (≥ 3.0.0)
Published: 2025-11-07
DOI: 10.32614/CRAN.package.opImputation (may not be active yet)
Author: Jorn Lotsch ORCID iD [aut, cre], Alfred Ultsch ORCID iD [aut]
Maintainer: Jorn Lotsch <j.lotsch at em.uni-frankfurt.de>
License: GPL-3
URL: https://github.com/JornLotsch/opImputation
NeedsCompilation: no
Materials: README
CRAN checks: opImputation results

Documentation:

Reference manual: opImputation.html , opImputation.pdf

Downloads:

Package source: opImputation_0.6.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): opImputation_0.6.tgz

Linking:

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