pmin(x, 60) and subset regression Is there any difference between
y ~ pmin(x, 60) + sex , df = data

and
y ~ x + sex, df = subset(data, x <=60)

If they are the same, then why use pmin(x, 60)

pmin will replace all instances of x greater than 60 by 60, and leave the vector x of the same length as it was before applying pmin. On the other hand, subset will filter the data, so it will reduce the sample size to those units satisfying the subsetting condition. Hence, the two datasets are, in general, different.
Here is a simple example.
set.seed(25)

# generate some data
dd <- data.frame(x = c(1,3,60, 5, 100, 7, 200), 
                 sex = c("M", "F", "M", "F", "F", "M", "F"),
                 y = runif(7))

# "pmined" data
dd2 <- dd
dd2$x <- pmin(dd$x, 60)

# filtered data
> subset(dd, x<= 60)
   x sex         y
1  1   M 0.4161184
2  3   F 0.6947637
3 60   M 0.1488006
4  5   F 0.8973850
6  7   M 0.9851157


# "pminded" data
> dd2

  x sex         y
1  1   M 0.4161184
2  3   F 0.6947637
3 60   M 0.1488006
4  5   F 0.8973850
5 60   F 0.1243921
6  7   M 0.9851157
7 60   F 0.6260962

