Creating categorical variables from mutually exclusive dummy variables

Question

My question regards an elaboration on a previously answered question about combining multiple dummy variables into a single categorical variable.

In the question p

Answer 1

Update (2019): Please use dplyr::coalesce(), it works pretty much the same.

My R package has a convenience function that allows to choose the first non-NA value for each element in a list of vectors:

#library(devtools)
#install_github('kimisc', 'muelleki')
library(kimisc)

df$factor1 <- with(df, coalesce.na(conditionA, conditionB))

(I'm not sure if this works if conditionA and conditionB are factors. Convert them to numerics before using as.numeric(as.character(...)) if necessary.)

Otherwise, you could give interaction a try, combined with recoding of the levels of the resulting factor -- but to me it looks like you're more interested in the first solution:

df$conditionAB <- with(df, interaction(coalesce.na(conditionA, 0), 
                                       coalesce.na(conditionB, 0)))
levels(df$conditionAB) <- c('A', 'B')