Function within loop with if statement in R - r

Question

I am not familiar with if statements/loops/or functions in R. I have a dataset where I want to adjust the a variable (N) by the clustering of the study (the formula is this one: N/(1 + (M - 1) * ICC). Where N is the number of subjects, the M is the size of the cluster and ICC is the intra-class correlation coeff. I have all these variables in separate columns with each row identifying the different studies/sample sizes. Not all the studies have a clustering issues so I need to apply this function only to the subset of those with the ICC. I thought about something like this but I know it is missing something, and also, I don't know if a loop with an if statement is the most efficient way to go.
for (i in df$N) { # for every sample size in df$N
if (df$ICC[i] != .) { # if ICC is not missing
df$N/(1 + (df$M - 1) * df$ICC) # adjust the sample size by dividing the N by the size
of the cluster - 1 and multiply per the ICC of the study
} else {
df$N/1 #otherwise (ICC is missing) do nothing: ie., divide the N by 1.
}
}
Do you know how I could do this with something like this? Other solutions are also welcome! Thanks for any help or suggestion about this!
Here's an example of the dataset:
dput(head(df, 10))
structure(list(ID = c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5), ArmsID = c(0,
1, 0, 1, 0, 1, 0, 1, 0, 1), N = c(26, 34, 28, 27, 50, 52, 60,
65, 150, 152), Mean = c(10.1599998474121, 5.59999990463257, 8,
8.52999973297119, 17, 15.1700000762939, 48.0999984741211, 49,
57, 55.1315803527832), SD = c(6.30000019073486, 4.30000019073486,
5.6, 6.61999988555908, 6, 7.75, 10.1599998474121, 12, 11, 10.5495901107788
), SE = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ICC = c(0.03,
0.02, NA, NA, 0.01, 0.003, NA, NA, NA, NA), M = c(5, 5, NA, NA,
17, 16, NA, NA, NA, NA)), row.names = c(NA, -10L), class = c("tbl_df",
"tbl", "data.frame"))
The . meant to indicate missing data: NA. I want to apply the functions that adjust the N only to the rows that have an ICC.
idx <- which(!is.na(df$ICC))
df$N[idx] <- df$N[idx]/(1 + (df$M[idx] - 1) * df$ICC[idx])
This code correctly works, thanks!