Package: remiod 1.0.2
Tony Wang
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) <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.
Authors:
remiod_1.0.2.tar.gz
remiod_1.0.2.tar.gz(r-4.5-noble)remiod_1.0.2.tar.gz(r-4.4-noble)
remiod_1.0.2.tgz(r-4.4-emscripten)remiod_1.0.2.tgz(r-4.3-emscripten)
remiod.pdf |remiod.html✨
remiod/json (API)
NEWS
# Install 'remiod' in R: |
install.packages('remiod', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/xsswang/remiod/issues
Last updated 2 years agofrom:153c41fa0d. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 01 2024 |
R-4.5-linux | OK | Dec 01 2024 |
Exports:extract_MIdataget_subsetlist.modelsmcmcplotmiAnalyzeremiodsummary
Dependencies:briocallrclicodacodetoolscolorspacecrayondata.tabledescdiffobjdigestdoFutureellipseevaluatefansifarverfftwtoolsforeachfsfuturefuture.applyggplot2globalsgluegtableisobanditeratorsJointAIjsonlitelabelinglatticelifecyclelistenvmagrittrMASSmathjaxrMatrixmcmcsemgcvmunsellnlmenumDerivordinalparallellypillarpkgbuildpkgconfigpkgloadpraiseprocessxprogressrpsR6RColorBrewerRcppRcppArmadillorjagsrlangrprojrootscalessurvivaltestthattibbleucminfutf8vctrsviridisLitewaldowithr
Example: Binary data imputation
Rendered fromExampleBinary.html.asis
usingR.rsp::asis
on Dec 01 2024.Last update: 2022-11-18
Started: 2022-11-18
Example: Continuous data imputation through GLM
Rendered fromExampleGauss.html.asis
usingR.rsp::asis
on Dec 01 2024.Last update: 2022-11-18
Started: 2022-11-18
Introduction to remiod
Rendered fromintroremiod.html.asis
usingR.rsp::asis
on Dec 01 2024.Last update: 2022-11-18
Started: 2022-11-18