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st: RE: Dividing a dataset


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Dividing a dataset
Date   Wed, 12 Apr 2006 13:35:22 +0100

bysort id1 (id) : gen byte which = _n 

Nick 
n.j.cox@durham.ac.uk 

miguel.ampudia@bde.es
 
> 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.

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