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

I think this function gives you what you need (admittedly, this is a quick hack).

to_indicator <- function(x, grp)
{
    apply(tbl, 1,
          function (x)
          {
              idx <- which(!is.na(x))
              nm <- names(idx)
              if (nm %in% grp)
                x[idx]
              else
                NA
          })
}

And here is it's used with the example data you provide.

tbl <- read.table(header=TRUE, text="
conditionA    conditionB    conditionC     conditionD
NA            1             NA             NA
1             NA            NA             NA
NA            NA            1              NA
NA            NA            NA             1
NA            2             NA             NA
2             NA            NA             NA
NA            NA            2              NA
NA            NA            NA             2")
tbl <- data.frame(tbl)

(tbl <- cbind(tbl,
              factor1=to_indicator(tbl, c("conditionA", "conditionB")),
              factor2=to_indicator(tbl, c("conditionC", "conditionD"))))