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 |
| In views: | ClinicalTrials |
| CRAN checks: | remiod results |
Documentation:
| Reference manual: | remiod.html , remiod.pdf |
| Vignettes: |
Example: Binary data imputation (source) Example: Continuous data imputation through GLM (source) Introduction to remiod (source) |
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 |
Linking:
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