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ggmice

Visualizations formice withggplot2

Enhance amiceimputation workflow with visualizations for incomplete and/or imputeddata. Theggmice functions produceggplotobjects which may be easily manipulated or extended. Useggmice to inspect missing data, develop imputation models,evaluate algorithmic convergence, or compare observed versus imputeddata.

Installation

You can install the latestggmice release fromCRAN with:

install.packages("ggmice")

Alternatively, you could install the development version ofggmice fromGitHubwith:

# install.packages("devtools")devtools::install_github("amices/ggmice")

Example

Inspect the missing data in an incomplete dataset and subsequentlyevaluate the imputed data points against observed data. See theGet startedvignette for an overview of all functionalities. Example data frommice,showing height (in cm) by age (in years).

# load packageslibrary(ggplot2)library(mice)library(ggmice)# load some datadat<- boys# visualize the incomplete dataggmice(dat,aes(age, hgt))+geom_point()

# impute the incomplete dataimp<-mice(dat,m =1,seed =1)# visualize the imputed dataggmice(imp,aes(age, hgt))+geom_point()

Acknowledgements

Theggmice package is developed with guidance andfeedback from theAmices team.Theggmice hex is based on theggplot2andmice hexdesigns.

This project has received funding from the European Union’s Horizon2020 research and innovation programme under ReCoDID grant agreement No825746.

Code of Conduct

You are invited to join the improvement and development ofggmice. Please note that the project is released with aContributor Codeof Conduct. By contributing to this project, you agree to abide byits terms.