Summarize outcomes into new variables

An example

Suppose you have a fairly detailed set of outcomes for cause of death. You want to summarize these outcomes into categories and create new variables indicating whether a person’s death could be attributed to a particular category or not. For example, suppose deaths from fentanyl are recorded as one of:

• Fentanyl Intoxication
• Fentanyl and Morphine Intoxication
• Combined Drug Intoxication (Heroin, Cocaine and Fentanyl)
• Fentanyl-involved

These are all possiblities in your dataset under a variable Cause_of_death. We will create a new variable, Fentanyl, that is a boolean variable which is TRUE if the person’s death is fentanyl-related and FALSE if it isn’t.

Approach 1

This is a general approach. First make a vector of all the possible ways fentanyl-related deaths are records:

fentanyl_related <- c('Fentanyl Intoxication', 'Fentanyl and Morphine Intoxication',
                      'Combined Drug Intoxication (Heroin, Cocaine and Fentanyl)',
                      'Fentanyl-involved')

We then can create the new variable quite easily as

dat <- dat %>% mutate(Fentanyl = Cause_of_death %in% fentanyl_related)

Approach 2

This approach leverages the text processing capabilities of the stringr package. We note that all the outcomes in fentanyl_related have the word “Fentanyl” in it. So we can create the Fentanyl variable using the following code:

dat <- dat %>% 
  mutate(Fentanyl = stringr::str_detect(Cause_of_death, 'Fentanyl'))

We could also protect ourselves against possible recording errors (in terms of capitalization) by making all the entries lower-case and then testing for the lower-case “fentanyl”. This avoids the issues with ignore.case that are required for the grep family of functions.

dat <- dat %>% 
  mutate(Fentanyl = stringr::str_detect(tolower(Cause_of_death), 'fentanyl'))