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>.

Package details

AuthorCraig Gower-Page [aut, cre], Alessandro Noci [aut], Marcel Wolbers [ctb], Roche [cph, fnd]
MaintainerCraig Gower-Page <craig.gower-page@roche.com>
LicenseApache License (>= 2)
URL https://insightsengineering.github.io/rbmi/ https://github.com/insightsengineering/rbmi
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the rbmi package in your browser

Any scripts or data that you put into this service are public.

rbmi documentation built on Nov. 24, 2023, 5:11 p.m.