Package: mlmi 1.1.2

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>.

Authors:Jonathan Bartlett

mlmi_1.1.2.tar.gz
mlmi_1.1.2.zip(r-4.5)mlmi_1.1.2.zip(r-4.4)mlmi_1.1.2.zip(r-4.3)
mlmi_1.1.2.tgz(r-4.5-any)mlmi_1.1.2.tgz(r-4.4-any)mlmi_1.1.2.tgz(r-4.3-any)
mlmi_1.1.2.tar.gz(r-4.5-noble)mlmi_1.1.2.tar.gz(r-4.4-noble)
mlmi_1.1.2.tgz(r-4.4-emscripten)mlmi_1.1.2.tgz(r-4.3-emscripten)
mlmi.pdf |mlmi.html
mlmi/json (API)
NEWS

# Install 'mlmi' in R:
install.packages('mlmi', repos = c('https://jwb133.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jwb133/mlmi/issues

Datasets:
  • ctsTrialWide - Simulated example data with continuous outcome measured repeatedly over time

On CRAN:

Conda:

2.70 score 10 scripts 208 downloads 7 exports 8 dependencies

Last updated 2 years agofrom:e04bde8130. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 24 2025
R-4.5-winNOTEMar 24 2025
R-4.5-macNOTEMar 24 2025
R-4.5-linuxNOTEMar 24 2025
R-4.4-winNOTEMar 24 2025
R-4.4-macNOTEMar 24 2025
R-4.4-linuxNOTEMar 24 2025
R-4.3-winOKMar 24 2025
R-4.3-macOKMar 24 2025

Exports:catImpmixImpnormImpnormUniImprefBasedCtsscoreBasedwithinBetween

Dependencies:catgsllatticeMASSMatrixmixnlmenorm