ggmice
mice
with ggplot2
Enhance a mice
imputation workflow with visualizations for incomplete and/or imputed
data. The ggmice
functions produce ggplot
objects which may be easily manipulated or extended. Use
ggmice
to inspect missing data, develop imputation models,
evaluate algorithmic convergence, or compare observed versus imputed
data.
You can install the latest ggmice
release from CRAN with:
install.packages("ggmice")
Alternatively, you could install the development version of
ggmice
from GitHub
with:
# install.packages("devtools")
::install_github("amices/ggmice") devtools
Inspect the missing data in an incomplete dataset and subsequently
evaluate the imputed data points against observed data. See the Get started
vignette for an overview of all functionalities. Example data from mice
,
showing height (in cm) by age (in years).
# load packages
library(ggplot2)
library(mice)
library(ggmice)
# load some data
<- boys
dat # visualize the incomplete data
ggmice(dat, aes(age, hgt)) + geom_point()
# impute the incomplete data
<- mice(dat, m = 1, seed = 1)
imp # visualize the imputed data
ggmice(imp, aes(age, hgt)) + geom_point()
The ggmice
package is developed with guidance and
feedback from the Amices team.
The ggmice
hex is based on the ggplot2
and mice
hex
designs.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under ReCoDID grant agreement No 825746.
You are invited to join the improvement and development of
ggmice
. Please note that the project is released with a Contributor Code
of Conduct. By contributing to this project, you agree to abide by
its terms.