Hello,
If you want Age quantiles by gender, you have to split the data by
gender, apply the same code then recombine the result.
fun <- function(x){
Age_group <- cut(x[, "Age"], labels=c(1:10),
breaks=quantile(x[, "Age"], seq(0,1,.1)),
include.lowest = TRUE)
cbind(x, Age_group)
}
result <- do.call(rbind, lapply(split(dat, dat[, "GENDER"]), fun))
rownames(result) <- seq_len(nrow(result))
result
Hope this helps,
Rui Barradas
Em 30-11-2012 12:18, R Kozarski escreveu:
Dear R users,
given the patient sample with their Gender and Age
GENDER Age
[1,] 2 45
[2,] 1 58
[3,] 1 54
[4,] 2 71
[5,] 2 64
...
I would like to create an another column which groups the patients wrt
Gender specific Age quantiles, following methodology similar to:
Age_group <- cut(Age, labels=c(1:10), breaks=quantile(Age,
seq(0,1,.1)),include.lowest = TRUE)
The function above allows me to group only wrt Age quantiles.
Best, Robert
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