I'm trying to reverse score (recode) some items in a dataframe. All reverse scored items end in an R, and each scale has a unique start ("hc", "out", and "hm"). I normally would just select all variables that end with an "r", but the issue is that some scales are on a 5-point scale ("hc" and "out") and others are on a 7-point scale ("hm").
Here is a sample of the much, much larger dataset:
library(tidyverse)
data <- tibble(name = c("Mike", "Ray", "Hassan"),
hc_1 = c(1, 2, 3),
hc_2r = c(5, 5, 4),
out_1r = c(5, 4, 2),
out_2 = c(2, 4, 5),
out_3r = c(2, 2, 1),
hm_1 = c(6, 7, 7),
hm_2r = c(7, 1, 7))
Let's say that I want to do this one scale at a time, so I start with hm, which is on a seven-point scale.
I want to try something like this with an & statement, but I get an error:
library(tidyverse)
library(car)
data %>%
mutate_at(vars(ends_with("r") & starts_with("hm")), ~(recode(., "1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1")))
Error:
ends_with("r") & starts_with("hc")must evaluate to column positions or names, not a logical vector
What's a clean way to make it perform the reverse scoring on these few variables at a time? Once again, the dataset is too big too practically select individual variables at a time.
Thanks!
It would be easier to use matches here
library(tidyverse)
data %>%
mutate_at(vars(matches("^hm.*r$")), ~(recode(.,
"1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1")))