_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-micemd 1.10.0
Propagated dependencies: r-pbivnorm@0.6.0 r-nlme@3.1-166 r-mvtnorm@1.3-2 r-mvmeta@1.0.3 r-mixmeta@1.2.0 r-mice@3.16.0 r-mgcv@1.9-1 r-matrix@1.7-1 r-mass@7.3-61 r-lme4@1.1-35.5 r-jomo@2.7-6 r-gjrm@0.2-6.7 r-digest@0.6.37 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/m.scm (guix-cran packages m)
Home page: https://cran.r-project.org/package=micemd
Licenses: GPL 2 GPL 3
Synopsis: Multiple Imputation by Chained Equations with Multilevel Data
Description:

Addons for the mice package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for mice'.

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