rbmi: Reference Based Multiple Imputation

Implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) <doi:10.21105/joss.04251>). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) <doi:10.1002/pst.2234>, Bayesian multiple imputation as described in Carpenter et al. (2013) <doi:10.1080/10543406.2013.834911>, and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) <doi:10.1214/20-STS793>.

Version: 1.6.0
Depends: R (≥ 3.4.0)
Imports: mmrm, pkgload, Matrix, tools, methods, R6, assertthat, jinjar, fs, stringr
Suggests: dplyr, tidyr, nlme, testthat, emmeans, tibble, mvtnorm, knitr, rmarkdown, bookdown, lubridate, purrr, ggplot2, rstan (≥ 2.26.0), R.rsp, withr
Published: 2026-01-23
DOI: 10.32614/CRAN.package.rbmi
Author: Lukas A. Widmer [aut, cre], Craig Gower-Page [aut], Isaac Gravestock [aut], Alessandro Noci [aut], Marcel Wolbers [ctb], Daniel Sabanes Bove [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Lukas A. Widmer <lukas_andreas.widmer at novartis.com>
BugReports: https://github.com/openpharma/rbmi/issues
License: Apache License (≥ 2)
URL: https://openpharma.github.io/rbmi/, https://github.com/openpharma/rbmi
NeedsCompilation: no
Citation: rbmi citation info
Materials: README, NEWS
CRAN checks: rbmi results

Documentation:

Reference manual: rbmi.html , rbmi.pdf
Vignettes: rbmi: Inference with Conditional Mean Imputation (source)
rbmi: Advanced Functionality (source)
rbmi: Quickstart (source)
rbmi: Statistical Specifications (source)

Downloads:

Package source: rbmi_1.6.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Old sources: rbmi archive

Reverse dependencies:

Reverse suggests: junco

Linking:

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