glemb: Multiple Imputation Using the General Location Model with the EMB Algorithm

Provides multiple imputation for mixed continuous and categorical data using the General Location Model (Olkin and Tate (1961) <doi:10.1214/aoms/1177705052>; Little and Schluchter (1985) <doi:10.1093/biomet/72.3.497>) combined with the Expectation-Maximization with Bootstrapping (EMB) algorithm of Honaker, King and Blackwell (2011) <doi:10.18637/jss.v045.i07>. Categorical variables are specified via the noms option; all other variables are treated as continuous. The package wraps the EM implementation in the 'mix' package and extends it with a bootstrap wrapper to produce proper multiple imputations in the sense of Rubin (1987, ISBN:978-0-471-08705-2).

Version:	0.1.4
Depends:	R (≥ 4.0.0)
Imports:	mix
Suggests:	mice, mitml, testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-10-15
DOI:	10.32614/CRAN.package.glemb (may not be active yet)
Author:	Paul Allison [aut, cre]
Maintainer:	Paul Allison <allison at statisticalhorizons.com>
BugReports:	https://github.com/pauldallison/glemb/issues
License:	GPL-3
URL:	https://github.com/pauldallison/glemb
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	glemb results

Documentation:

Reference manual:	glemb.html , glemb.pdf
Vignettes:	Introduction to glemb (source, R code)

Downloads:

Package source:	glemb_0.1.4.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): glemb_0.1.4.tgz, r-oldrel (x86_64): glemb_0.1.4.tgz

Linking:

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