Assigning NAs to values in a list - r

Question

I have a data frame that includes many variables. Here is a shortened version of what I have so far:
n_20010_0_0 <- c(1,2,3,4)
n_20010_0_1 <- c(0, -2, NA, 4)
n_20010_0_2 <- c(3, 0, -7, 2)
x <- data.frame (n_20010_0_0, n_20010_0_1, n_20010_0_2)
I created a new variable that returns whether or not there is a 1 within the list of variables:
MotherIllness0 <- paste("n_20010_0_", 0:2, sep = "")
x$MotherCAD_0_0 <- apply(x, 1, function(x) as.integer(any(x[MotherIllness0] == 1, na.rm = TRUE)))
I would like to keep the NAs as 0's, but I would also like to recode it so that if there is a -7 the new value is NA.
This is what I've tried and it doesn't work:
x$MotherCAD_0_0[MotherIllness0 == -7] <- NA

Answer 1

you don't need to define MotherIllness0, the argument 1 in your apply function takes care of that.
Here's a line of code that does both things you want.
MotherIllness0 <- paste("n_20010_0_", 0:2, sep = "")
x$MotherCAD_0_0<- apply(x[,MotherIllness0], 1, function(x) ifelse(any(x==-7), NA,
as.integer(any(x==1, na.rm=T))))
I assumed that a row with both 1s and -7s should have NA for the new variable. If not, then this should work:
x$MotherCAD_0_0<- apply(x[,MotherIllness0], 1, function(x) ifelse(any(x==1, na.rm=T), 1,
ifelse(any(x==-7), NA, 0)))
Note that with the example you have above, these two lines should produce the same outcome.

Answer 2

Here's another way to do it, without using any if-else logic:
# Here's your dataset, with a row including both 1 and -7 added:
x <- data.frame (n_20010_0_0 = c(1, 2, 3, 4, 1),
n_20010_0_1 = c(0, -2, NA, 4, 0) ,
n_20010_0_2 = c(3, 0, -7, 2, -7)
)
# Your original function:
MotherIllness0 <- paste("n_20010_0_", 0:2, sep = "")
x$MotherCAD_0_0 <- apply(x, MARGIN = 1, FUN = function(x) {
as.integer(
any(x[MotherIllness0] == 1, na.rm = TRUE)
)
})
# A simplified version
x$test <- apply(x, MARGIN = 1, FUN = function(row) {
as.integer(
any(row[MotherIllness0] == 1, na.rm = TRUE) &
!any(row[MotherIllness0] == -7, na.rm = TRUE)
)
})
A couple of notes: the name of x in an anonymous function like function(x) can be anything, and you'll save yourself a lot of confusion by calling it what it is (I named it row above).
It's also unlikely that you actually need to convert your result column to integer - logical columns are easier to interpret, and they work the same as 0-1 columns for just about everything (e.g., TRUE + FALSE equals 1).