Package: mlmi 1.1.4
mlmi: Maximum Likelihood Multiple Imputation
Implements proper and so-called Maximum Likelihood Multiple Imputation as described by von Hippel and Bartlett (2021) <doi:10.1214/20-STS793>. A number of different imputation methods are available, by utilising the 'norm', 'cat' and 'mix' packages. Inferences can be performed either using Rubin's rules (for proper imputation), or a modified version for maximum likelihood imputation. For maximum likelihood imputations a likelihood score based approach based on theory by Wang and Robins (1998) <doi:10.1093/biomet/85.4.935> is also available.
Authors:
mlmi_1.1.4.tar.gz
mlmi_1.1.4.zip(r-4.7)mlmi_1.1.4.zip(r-4.6)mlmi_1.1.4.zip(r-4.5)
mlmi_1.1.4.tgz(r-4.6-any)mlmi_1.1.4.tgz(r-4.5-any)
mlmi_1.1.4.tar.gz(r-4.7-any)mlmi_1.1.4.tar.gz(r-4.6-any)
mlmi_1.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mlmi/json (API)
| # 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
- ctsTrialWide - Simulated example data with continuous outcome measured repeatedly over time
Last updated from:b886828d1a. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 156 | ||
| source / vignettes | OK | 169 | ||
| linux-release-x86_64 | OK | 151 | ||
| macos-release-arm64 | OK | 85 | ||
| macos-oldrel-arm64 | OK | 103 | ||
| windows-devel | OK | 111 | ||
| windows-release | OK | 113 | ||
| windows-oldrel | OK | 95 | ||
| wasm-release | OK | 113 |
Exports:catImpmixImpnormImpnormUniImprefBasedCtsscoreBasedwithinBetween
