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>.
Package details |
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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@roche.com> |
License | Apache License (>= 2) |
Version | 1.3.0 |
URL | https://insightsengineering.github.io/rbmi/ https://github.com/insightsengineering/rbmi |
Package repository | View on CRAN |
Installation |
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