mlmi implements so called Maximum Likelihood Multiple Imputation as described by von Hippel (2018) https://arxiv.org/abs/1210.0870v9. A number of different imputations are available, by utilising the norm, cat and mix packages. Inferences can be performed either using combination rules similar to Rubin’s or using a likelihood score based approach based on theory by Wang and Robins (1998) https://doi.org/10.1093/biomet/85.4.935.

You can install the released version of bootImpute from CRAN with: install.packages(“mlmi”)

And the development version with install.packages(“devtools”) devtools::install_github(“jwb133/mlmi”)