mlmi

Implements so called Maximum Likelihood Multiple Imputation as described by von Hippel and Bartlett (2021) doi:10.1214/20-STS793. 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) doi:10.1093/biomet/85.4.935.