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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