insightsengineering/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

Package details

Maintainer
LicenseApache License (>= 2)
Version1.4.1
URL https://insightsengineering.github.io/rbmi/ https://github.com/insightsengineering/rbmi
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("insightsengineering/rbmi")
insightsengineering/rbmi documentation built on Feb. 28, 2025, 3:34 a.m.