Formatting exam results to perform a t-test in R - r

Question

Question Overview: I have a dataset containing the results to a 15 question pre-instructional and post-instructional exam. I am looking to run a t-test on the results to compare the overall means but am having difficulty formatting the dataset properly. An example portion of the Dataset is given below:
1Pre 1Post 2Pre 2Post 3Pre 3Post 4Pre 4Post
Correct B B A A B B C C
1 B B C D C B C C
2 C B B D C B C A
3 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
4 B B B A B B C C
5 B B B A B B C C
6 C B D A A D C B
7 C C D D E E C C
8 C A B B A A <NA> <NA>
Objective: I would like to match the "Correct" value to the values in the rows below for the test takers, such that a value of 1 is correct, and a value of 0 is incorrect. I have accomplished this using the following code:
for(j in 1:ncol(qDat)){
for(i in 1:nrow(qDat)){
if(qDat[i,j] == correctAns[1]){
qDat[i,j]=1
}else{
qDat[i,j]=0
}
}
}
I would then like to run a t-test comparing the pre and post means in addition to comparing the difference between the pre and post scores from each question, however, I need to omit any data points with NA. Currently, my method does not work with any NA values and thus replaces them with zero. Is there any method of running these tests and simply omitting NA values? Thank you!
The Desired Output:
1Pre 1Post 2Pre 2Post 3Pre 3Post
Correct B B A A B B
1 1 1 0 0 0 1
2 0 1 0 0 0 1
3 <NA> <NA> <NA> <NA> <NA> <NA>
4 1 1 0 0 1 1
5 1 1 0 0 1 1
6 0 1 0 1 0 0
7 0 0 0 0 0 0
8 0 0 0 0 0 0

Answer 1

You can try passing the following argument to the t.test call:
na.action = na.omit
Something like:
with(qDat, t.test(`1Pre`, `1Post`, na.action = na.omit))

Answer 2

What about this:
rewrote your loop - no need to worry to much about NAs as you treat them as 0, we can simply test the results and after set NAs as FALSE:
test <- qDat == correctAns # or correctAns[1] depending on your needs
test[is.na(test)] <- FALSE
storage.mode(test) <- "integer"
test
# X1 X2 X3 X4 X5 X6 X7 X8
# [1,] 0 1 0 0 1 0 1 0
# [2,] 0 0 1 0 0 0 0 0
# [3,] 0 1 0 0 1 0 0 0
# [4,] 0 0 1 0 0 0 0 0
# [5,] 1 0 0 0 0 0 1 0
# [6,] 0 0 1 1 1 1 1 0
# [7,] 0 0 0 1 0 0 1 0
# [8,] 0 0 0 0 0 0 0 1
with the data
set.seed(123)
correctAns <- sample(LETTERS[1:3], 8, replace = TRUE)
correctAns
# [1] "A" "C" "B" "C" "C" "A" "B" "C"
qDat <- sample(c(LETTERS[1:3], NA_character_), 8*2*4, replace = TRUE)
qDat <- data.frame(matrix(qDat, 8, 4*2), stringsAsFactors = FALSE)
qDat
# X1 X2 X3 X4 X5 X6 X7 X8
# 1 C A C C A B A <NA>
# 2 B A C <NA> B <NA> <NA> B
# 3 <NA> B C A B A <NA> <NA>
# 4 B <NA> C B B B B <NA>
# 5 C <NA> B <NA> A <NA> C <NA>
# 6 C C A A A A A B
# 7 A C <NA> B A C B <NA>
# 8 <NA> <NA> <NA> A B A B C
Edit
set.seed(123)
# correctAns is a vector of length 30
correctAns <- sample(LETTERS[1:3], 30, replace = TRUE)
length(correctAns)
# [1] 30
# qDat is a dataframe of dimensions 106x30
qDat <- sample(c(LETTERS[1:3], NA_character_), 106*30, replace = TRUE)
qDat <- data.frame(matrix(qDat, 106, 30), stringsAsFactors = FALSE)
dim(qDat)
# [1] 106 30
# still works
test <- qDat == correctAns
test[is.na(test)] <- FALSE
storage.mode(test) <- "integer"
str(test)
# int [1:106, 1:30] 0 0 0 0 0 0 0 0 1 0 ...
# - attr(*, "dimnames")=List of 2
# ..$ : NULL
# ..$ : chr [1:30] "X1" "X2" "X3" "X4" ...