So basically I want to turn a numeric income variable into an ordinal income variable where the cut-off points for the categories are decided so that each category ends up with the same N (or 1 less for one of the categories if it's an odd number N, to begin with).
Does anyone know how I can do this in R?
Here's an example using mtcars.
I'd suggest you use the ntile function that splits your variable into groups with the same number of cases.
Assume that the variable of interest is disp:
library(dplyr)
mtcars %>%
group_by(g = ntile(disp, 3)) %>% # split variable into 3 groups
mutate(g_range = paste0(min(disp), "-", max(disp))) %>% # create the ranges
ungroup() -> df
Your updated data (df) will look like this:
# # A tibble: 32 x 13
# mpg cyl disp hp drat wt qsec vs am gear carb g g_range
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <chr>
# 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 2 146.7-301
# 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 2 146.7-301
# 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 1 71.1-145
# 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 2 146.7-301
# 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 3 304-472
# 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 2 146.7-301
# 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 3 304-472
# 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 2 146.7-301
# 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 1 71.1-145
#10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 2 146.7-301
# # ... with 22 more rows
You can check the number of cases within each group:
df %>% count(g, g_range)
# # A tibble: 3 x 3
# g g_range n
# <int> <chr> <int>
# 1 1 71.1-145 11
# 2 2 146.7-301 11
# 3 3 304-472 10