remiod: Reference-Based Multiple Imputation for Ordinal/Binary Response

Reference-based multiple imputation of ordinal and binary responses under Bayesian framework, as described in Wang and Liu (2022) <doi:10.48550/arXiv.2203.02771>. Methods for missing-not-at-random include Jump-to-Reference (J2R), Copy Reference (CR), and Delta Adjustment which can generate tipping point analysis.

Version:	1.0.2
Depends:	R (≥ 2.10)
Imports:	JointAI, rjags, coda, foreach, data.table, future, doFuture, mathjaxr, survival, ggplot2, ordinal, progressr, Matrix, mcmcse
Suggests:	knitr, rmarkdown, bookdown, R.rsp, ggpubr, testthat (≥ 3.0.0), spelling
Published:	2022-11-18
DOI:	10.32614/CRAN.package.remiod
Author:	Ying Liu [aut], Tony Wang [aut, cre]
Maintainer:	Tony Wang <xwang at imedacs.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/xsswang/remiod
NeedsCompilation:	no
SystemRequirements:	JAGS (http://mcmc-jags.sourceforge.net/)
Language:	en-US
Materials:	README NEWS
CRAN checks:	remiod results

Documentation:

Reference manual:	remiod.pdf
Vignettes:	Example: Binary data imputation Example: Continuous data imputation through GLM Introduction to remiod

Downloads:

Package source:	remiod_1.0.2.tar.gz
Windows binaries:	r-devel: remiod_1.0.2.zip, r-release: remiod_1.0.2.zip, r-oldrel: remiod_1.0.2.zip
macOS binaries:	r-release (arm64): remiod_1.0.2.tgz, r-oldrel (arm64): remiod_1.0.2.tgz, r-release (x86_64): remiod_1.0.2.tgz, r-oldrel (x86_64): remiod_1.0.2.tgz
Old sources:	remiod archive

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