Integration with R

If you don't want to use Julia for your data analysis, but you'd like to try out Mice.jl, good news - you can call R functions from Julia! The Julia package RCall.jl allows you to do this.

You can start in Julia, perform your data wrangling in R, use Mice.jl and then send your Mids object back to R and continue analysing it there. For example:

julia> using Mice, Random, RCall

# You can switch from Julia to R by entering $

R> data <- read.csv("test/data/cirrhosis.csv")

R> data$Stage <- as.factor(data$Stage)

# Return to Julia by pressing backspace

julia> @rget data

julia> predictorMatrix = makePredictorMatrix(data);
    
julia> predictorMatrix[:, ["ID", "N_Days"]] .= false;

julia> Random.seed!(1234); # Set random seed for reproducibility

julia> imputedData = mice(data, predictorMatrix = predictorMatrix);

julia> @rput imputedData

R> library(mice)

R> analyses <- with(imputedData, lm(N_Days ~ Drug + Age + Stage + Bilirubin))

R> results <- summary(pool(analyses))

Funded by Wellcome