r - partial imputation with missForest

Question

I'm trying to use the missForest package in R to partially impute a dataset. In detail, I would like to impute all the metric variables but leave a few columns alone. Is this possible?

Answer 1

I have a potential solution, if I'm understanding your question correctly. I am going to provide you some code that should be fully reproducible.

## Get some data...
data(iris)

## The data contains four continuous and one categorical variable.
## Artificially produce missing values using the 'prodNA' function:
set.seed(81)
iris.mis <- prodNA(iris, noNA = 0.1)

## Impute missing values for just the first four columns of data
iris.mis[,1:4] <- missForest(iris.mis)$ximp[,1:4]

Let me know if an approach like this works. If it doesn't work, see if you can use some example code to show why.