mlmi: Maximum Likelihood Multiple Imputation
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>.
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