ImputeLongiCovs: Longitudinal Imputation of Categorical Variables via a Joint Transition Model

Imputation of longitudinal categorical covariates. We use a methodological framework which ensures that the plausibility of transitions is preserved, overfitting and colinearity issues are resolved, and confounders can be utilized. See Mamouris (2023) <doi:10.1002/sim.9919> for an overview.

Version:	0.1.0
Depends:	R (≥ 3.4.4)
Imports:	nnet, stats
Suggests:	knitr, rmarkdown
Published:	2023-10-06
Author:	Pavlos Mamouris [aut, cre], Vahid Nassiri [aut, ctb], Geert Molenberghs [ctb], Geert Verbeke [ctb]
Maintainer:	Pavlos Mamouris <pavlos.k.mamouris at gmail.com>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	ImputeLongiCovs results

Documentation:

Reference manual:	ImputeLongiCovs.pdf
Vignettes:	Title of your vignette

Downloads:

Package source:	ImputeLongiCovs_0.1.0.tar.gz
Windows binaries:	r-devel: ImputeLongiCovs_0.1.0.zip, r-release: ImputeLongiCovs_0.1.0.zip, r-oldrel: ImputeLongiCovs_0.1.0.zip
macOS binaries:	r-release (arm64): ImputeLongiCovs_0.1.0.tgz, r-oldrel (arm64): ImputeLongiCovs_0.1.0.tgz, r-release (x86_64): ImputeLongiCovs_0.1.0.tgz, r-oldrel (x86_64): ImputeLongiCovs_0.1.0.tgz

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