Hi all,
I have a dataset with contains the results of a multiple imputation, so
each observation is contained 5 times. I'm trying to divide this dataset
into 5 different ones (one for each imputed dataset) but I cannot find
an easy way to do it.
My identification variables are 'id' and 'id1':
list id id1
+--------------+
| id id1 |
|--------------|
1. | 11 1 |
2. | 12 1 |
3. | 13 1 |
4. | 14 1 |
5. | 15 1 |
|--------------|
6. | 21 2 |
7. | 22 2 |
8. | 23 2 |
9. | 24 2 |
10. | 25 2 |
|--------------|
11. | 31 3 |
12. | 32 3 |
13. | 33 3 |
14. | 34 3 |
15. | 35 3 |
|--------------|.
=2E
The only thing i could think about is (if 3000 observations):
forvalues m=3D1/3000 {
forvalues n=3D2/5 {
drop if id =3D=3D `m'`n'
}
}
So i'll be keeping imputed dataset number 1. then repeat this for the
rest of datasets. As you can see this is slow and not really practical.
Is there a way it can be done easily?
Thanks.
Miguel
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