rbmi: Reference Based Multiple Imputation (original) (raw)
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: | 1.5.1 |
|---|---|
| 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: | 2025-10-14 |
| DOI: | 10.32614/CRAN.package.rbmi |
| Author: | Craig Gower-Page [aut, cre], Isaac Gravestock [aut], Alessandro Noci [aut], Marcel Wolbers [ctb], Daniel Sabanes Bove [aut], F. Hoffmann-La Roche AG [cph, fnd] |
| Maintainer: | Craig Gower-Page <craig.gower-page at novartis.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 [issues need fixing before 2025-10-29] |
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