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:	1.3.0
Depends:	R (≥ 3.4.0)
Imports:	mmrm, pkgload, Matrix, tools, methods, R6, assertthat
Suggests:	dplyr, tidyr, nlme, testthat, emmeans, tibble, mvtnorm, knitr, rmarkdown, bookdown, lubridate, purrr, ggplot2, rstan (≥ 2.26.0), R.rsp
Published:	2024-10-16
DOI:	10.32614/CRAN.package.rbmi
Author:	Craig Gower-Page [aut, cre], Alessandro Noci [aut], Marcel Wolbers [ctb], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer:	Craig Gower-Page <craig.gower-page at roche.com>
BugReports:	https://github.com/insightsengineering/rbmi/issues
License:	Apache License (≥ 2)
URL:	https://insightsengineering.github.io/rbmi/, https://github.com/insightsengineering/rbmi
NeedsCompilation:	no
Citation:	rbmi citation info
Materials:	README NEWS
In views:	ClinicalTrials
CRAN checks:	rbmi results

Documentation:

Reference manual:	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_1.3.0.tar.gz
Windows binaries:	r-devel: rbmi_1.3.0.zip, r-release: rbmi_1.3.0.zip, r-oldrel: rbmi_1.3.0.zip
macOS binaries:	r-release (arm64): rbmi_1.2.6.tgz, r-oldrel (arm64): rbmi_1.3.0.tgz, r-release (x86_64): rbmi_1.2.6.tgz, r-oldrel (x86_64): rbmi_1.3.0.tgz
Old sources:	rbmi archive

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