I am working with data from the National Health Interview Survey and trying to simplify the race variable into 5 buckets. I want to create a new column titled "RACE" from existing data which includes Asian =1, Black=2, White (non-Hispanic)=3, Hispanic=4, Other=5. Currently, the race variable is titled "RACEA" and includes several codes indicating race as written here:
411, 412, 416, 434= Asian
200=Black
100=White
310,580,600=Other
BUT, the variable indicating Hispanic ethnicity is a separate variable titled HISPETH. With this variable,
10=non-Hispanic
20,23,30,40,50,61,62,63,70=Hispanic
Therefore, to create the white (non-Hispanic) and Hispanic value I need R to use both the column values of RACEA and HISPETH.
Here is the code I attempted to run in order to do all this, but I was met with the error message that "the longer the object length is not a multiple of shorter object length" for the portion with the list of HISPETH values as shown below.
What should I do? I am open to using other functions besides case_when, this is just what I've used in the past. Thanks!
`NHIS_test <- NHIS1 %>%
mutate(RACE = case_when(RACEA <= 411 ~ '1',
RACEA <= 412 ~ '1',
RACEA <= 416 ~ '1',
RACEA <= 434 ~ '1',
RACEA <= 200 ~ '2',
RACEA <= 100 & HISPETH <= 10 ~ '3',
HISPETH <= c(20:70) ~ '4',
RACEA<=100 & HISPETH <= c(20,23,30,40,50,61,62,63,70) ~ '4',
RACEA <= 310 ~ '5',
RACEA <= 580 ~ '5',
RACEA <= 600 ~ '5',
TRUE ~ 'NA'))`
To compare a single value you should use ==, to compare multiple values use %in%.
library(dplyr)
NHIS_test <- NHIS1 %>%
mutate(RACE = case_when(
RACEA %in% c(411, 412, 416, 434) ~ 1,
RACEA == 200 ~ 2,
RACEA == 100 & HISPETH == 10 ~ 3,
RACEA == 100 & HISPETH %in% c(20,23,30,40,50,61,62,63,70) ~ 4,
RACEA %in% c(310, 580, 600) ~ 5))
If none of the above condition is satisfied it will return NA by default.