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mice (3.18.0)

Published 2026-02-24 13:47:20 +00:00 by atheaadmin

Installation

Setup this registry in your Rprofile.site file:

options("repos" = c(getOption("repos"), c(gitea="")))

To install the package, run the following command:

install.packages("mice")

For more information on the CRAN registry, see the documentation.

About this package

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.Multivariate Imputation by Chained Equations

Dependencies

Imports	broom, dplyr, glmnet, graphics, grDevices, lattice, mitml, nnet, Rcpp, rpart, stats, tidyr, utils
Depends	R (>= 2.10.0)
LinkingTo	cpp11, Rcpp
Suggests	broom.mixed, future, furrr, haven, knitr, literanger, lme4, MASS, miceadds, pan, parallelly, purrr, ranger, randomForest, rmarkdown, rstan, survival, testthat

Details

CRAN

2026-02-24 13:47:20 +00:00

0

GPL (>= 2)

Stef van Buuren

Karin Groothuis-Oudshoorn

Gerko Vink

Rianne Schouten

Alexander Robitzsch

Patrick Rockenschaub

Lisa Doove

Shahab Jolani

Margarita Moreno-Betancur

Ian White

Philipp Gaffert

Florian Meinfelder

Bernie Gray

Vincent Arel-Bundock

Mingyang Cai

Thom Volker

Edoardo Costantini

Caspar van Lissa

Hanne Oberman

Stephen Wade

Project Site

Project Site

601 KiB

Assets (1)

mice_3.18.0.tar.gz 601 KiB

Versions (1) View all

3.18.0 2026-02-24