Need to transform output into a single vector in R - r

Question

I'm trying to write a function that performs a given number (n) of t-tests on a random set of normal data of size k. The output should be a count of the total number of significant (<0.05) t-tests and a ratio of significant to overall t-tests. I wrote this function below:
StatPractice <- function(n, k) {
i = 1
length <- k
size <- n
while(i <= size){
k1 <- rnorm(length)
k2 <- rnorm(length)
t <- t.test(k1, k2)
p <- cbind(t$p.value)
i <- i + 1;
q <- c(p <= 0.05)
count <- length(q[q==TRUE])
prop <- count/size
print(q)
}
cat("count of significant t-tests:", count, "\n",
"proportion of significant t-tests:", prop, "\n")
}
I've tooled with this in a number of ways, but essentially, the output is something like this:
[1] FALSE
[1] TRUE
[1] FALSE
[1] FALSE
[1] FALSE
[1] TRUE
[1] FALSE
[1] FALSE
[1] FALSE
[1] FALSE
count of significant t-tests: 0
proportion of significant t-tests: 0
Could someone help me figure out why the count is unable to recognize q as a single vector and thus unable to give correct output for number of TRUE values?

Answer 1

You need a vector to store the p-values. Currently, the object p stores the last value only. You can create a vector before the loop starts (p <- numeric(size)). Within the loop, you assign the current p-value to the vector p at index i (p <- numeric(size)). The counting of significant p-values has to be done after the loop. Below is a modified version of your function.
StatPractice <- function(n, k) {
i = 1
length <- k
size <- n
p <- numeric(size)
while(i <= size){
k1 <- rnorm(length)
k2 <- rnorm(length)
t <- t.test(k1, k2)
p[i] <- t$p.value
i <- i + 1
}
q <- p <= 0.05
count <- sum(q)
prop <- count/size
print(q)
cat("count of significant t-tests:", count, "\n",
"proportion of significant t-tests:", prop, "\n")
}
Note that length(q[q==TRUE]) has been replaced with the simpler command sum(q). Furthermore, the function does not print q but return q.