CRAN/E | remiod

remiod

Reference-Based Multiple Imputation for Ordinal/Binary Response

Installation

About

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

github.com/xsswang/remiod
System requirements JAGS (http://mcmc-jags.sourceforge.net/)

Key Metrics

Version 1.0.2
R ≥ 2.10
Published 2022-11-18 694 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks remiod results
Language en-US

Downloads

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Maintainer

Maintainer

Tony Wang

[email protected]

Authors

Ying Liu

aut

Tony Wang

aut / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

Example: Binary data imputation
Example: Continuous data imputation through GLM
Introduction to remiod

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

remiod archive

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
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