AddMissingIndicatorVariables: Add missing indicator variables function
In citronmeliss/predictionpackr: Predictionpackr

Creates missing indicator variables for each predictor variable (feature) with missing values

1 2	AddMissingIndicatorVariables(study.sample, outcome.name = "composite", features = NULL, excluded.columns = c("tc"))

`study.sample`	Data Frame. The study sample. No default
`outcome.name`	String. The name of outcome variable. Defaults to "composite"
`features`	Character vector. The names of the feature variables. Defaults to NULL, in which case all columns except outcome.name and those potentially listed in excluded.columns are treated as features.
`excluded.columns`	Character vector. The names of columns that should not be treated as features. Defaults to NULL and is then ignored. Is also ignored if features is specified.