stratified sampling or proportional sampling in R

Question

I have a data set generated as follows:

myData <- data.frame(a=1:N,b=round(rnorm(N),2),group=round(rnorm(N,4),0))

The data looks like as

Answer 1

You can use my stratified function, specifying a value < 1 as your proportion, like this:

## Sample data. Seed for reproducibility 
set.seed(1)
N <- 50
myData <- data.frame(a=1:N,b=round(rnorm(N),2),group=round(rnorm(N,4),0))

## Taking the sample
out <- stratified(myData, "group", .3)
out
#     a     b group
# 17 17 -0.02     2
# 8   8  0.74     3
# 25 25  0.62     3
# 49 49 -0.11     3
# 4   4  1.60     3
# 26 26 -0.06     4
# 27 27 -0.16     4
# 7   7  0.49     4
# 12 12  0.39     4
# 40 40  0.76     4
# 32 32 -0.10     4
# 9   9  0.58     5
# 42 42 -0.25     5
# 43 43  0.70     5
# 37 37 -0.39     5
# 11 11  1.51     6

Compare the counts in the final group with what we would have expected.

round(table(myData$group) * .3)
# 
# 2 3 4 5 6 
# 1 4 6 4 1 
table(out$group)
# 
# 2 3 4 5 6 
# 1 4 6 4 1 

---

You can also easily take a fixed number of samples per group, like this:

stratified(myData, "group", 2)
#     a     b group
# 34 34 -0.05     2
# 17 17 -0.02     2
# 49 49 -0.11     3
# 22 22  0.78     3
# 12 12  0.39     4
# 7   7  0.49     4
# 18 18  0.94     5
# 33 33  0.39     5
# 45 45 -0.69     6
# 11 11  1.51     6