dum2nom {quest}

Dummy Variables to a Nominal Variable

Description

dum2nom converts dummy variables to a nominal variable. The information from the dummy columns in a data.frame are combined into a character vector (or factor if rtn.fct = TRUE) representing a nominal variable. The unique values of the nominal variable will be the dummy colnames (i.e., dum.nm). Note, *all* the dummy variables associated with a nominal variable are required for this function to work properly. In regression-like models, data analysts will exclude one dummy variable for the category that is the reference group. If d = number of categories in the nominal variable, then that leads to d - 1 dummy variables in the model. dum2nom requires all d dummy variables.

Usage

dum2nom(data, dum.nm, yes = 1L, rtn.fct = FALSE)

Arguments

data

data.frame of data.

dum.nm

character vector of colnames from data specifying the dummy variables.

yes

atomic vector of length 1 specifying the unique value of the category in each dummy column. This must be the same value for all the dummy variables.

rtn.fct

logical vector of length 1 specifying whether the return object should be a factor (TRUE) or a character vector (FALSE).

Details

dum2nom tests to ensure that data[dum.nm] are indeed a set of dummy columns. First, the dummy columns are expected to have the same mode such that there is one yes unique value across the dummy columns. Second, each row in data[dum.nm] is expected to have either 0 or 1 instance of yes. If there is more than one instance of yes in a row, then an error is returned. If there is 0 instances of yes in a row (e.g., all missing values), NA is returned for that row. Note, any value other than yes will be treated as a no.

Value

character vector (or factor if rtn.fct = TRUE) containing the unique values of dum.nm - one for each dummy variable.

See Also

nom2dum

Examples

dum <- data.frame(
   "Quebec_nonchilled" = ifelse(CO2$"Type" == "Quebec" & CO2$"Treatment" == "nonchilled",
      yes = 1L, no = 0L),
   "Quebec_chilled" = ifelse(CO2$"Type" == "Quebec" & CO2$"Treatment" == "chilled",
      yes = 1L, no = 0L),
   "Mississippi_nonchilled" = ifelse(CO2$"Type" == "Mississippi" & CO2$"Treatment" == "nonchilled",
      yes = 1L, no = 0L),
   "Mississippi_chilled" = ifelse(CO2$"Type" == "Mississippi" & CO2$"Treatment" == "chilled",
      yes = 1L, no = 0L)
)
dum2nom(data = dum, dum.nm = names(dum)) # default
dum2nom(data = dum, dum.nm = names(dum), rtn.fct = TRUE) # return as a factor
## Not run: 
dum2nom(data = npk, dum.nm = c("N","P","K")) # error due to overlapping dummy columns
dum2nom(data = mtcars, dum.nm = c("vs","am"))# error due to overlapping dummy columns

## End(Not run)