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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>.
Getting started
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Package details |
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| Author | Craig Gower-Page [aut, cre], Alessandro Noci [aut], Marcel Wolbers [ctb], Roche [cph, fnd] |
| Maintainer | Craig Gower-Page <craig.gower-page@roche.com> |
| License | Apache License (>= 2) |
| Version | 1.2.6 |
| URL | https://insightsengineering.github.io/rbmi/ https://github.com/insightsengineering/rbmi |
| Package repository | View on CRAN |
| Installation |
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