Exercise 2_2_2: Define your Cases

library(tidyverse)
library(sjlabelled)

gp_covid <- 
  read_csv2("./data/ZA5667_v1-1-0.csv") %>%
  set_na(na = c(-99, -77, -33, 98))

1

Create a new binary variable called married in the gp_covid dataframe that has the value 1 if the individual is married and 0 if not.

Clues

As there are no missing values in the variable, you can simply use ifelse() for this.

2

Let’s create another new variable. This time, it should be a character variable named age_3cat that has the following unique values representing the respective age categories: “up to 40 years”, “41 to 60 years” and “older than 60 years”.

Clues

You can use the between() helper function in combination with the dplyr function for conditional variable creation/transformation. The required existing variable is called age_cat. As a side note: In reality, you would probably would want to have such a variable as an ordered factor, but for the sake of simplicity, we’ll stick with character variable here.