Martin - collapse was, in fact, the easiest path to the solution. I'm grateful for your advice!
Mark
On Dec 8, 2009, at 5:51 PM (12/8/09), Martin Weiss wrote:
>
> <>
>
> " It seems to be at the intersection of ideas behind reshape / stack"
>
>
>
> -reshape- does indeed look like a great solution here, but really your
> dataset is neither exactly "long" nor "wide"...
>
> -stack- seems a little far fetched. I rarely try to use it for this kind of
> data management problem...
>
> HTH
> Martin
>
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of Martin Weiss
> Sent: Dienstag, 8. Dezember 2009 23:39
> To: [email protected]
> Subject: st: RE: combining values distributed over multiple observations
>
>
> <>
>
> Could be as easy as
>
>
> *******
> clear*
>
> inp var:mylabel T1 T2 T3 T4 T5 , auto
> A .129 . . . .
> A . .647 . . .
> A . . .991 . .
> A . . . .582 .
> A . . . . .043
> end
>
> compress
>
> collapse (min) T?, by(var)
> list, noo
> *******
>
>
> HTH
> Martin
>
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of Mark Pachucki
> Sent: Dienstag, 8. Dezember 2009 23:35
> To: [email protected]
> Subject: st: combining values distributed over multiple observations
>
> Hello - this seems like an exceedingly simple question, but couldn't find a
> reference to relevant syntax in the help. What I'm essentially trying to do
> is go from the below format, where a given variable "A" takes different
> values at discrete observations arrayed over T1-T5:
>
> var T1 T2 T3 T4 T5
>
> A .129 . . . .
> A . .647 . . .
> A . . .991 . .
> A . . . .582 .
> A . . . . .043
>
>
> to the following format, wherein all values of A at each time are compressed
> into one observation :
>
> var T1 T2 T3 T4 T5
>
> A .129 .647 .991 .582 .043
>
> It seems to be at the intersection of ideas behind reshape / stack (and even
> stjoin - except it's not survival-time data). Yet doesn't fall neatly within
> any (or does it?)
>
> Thanks in advance,
> Mark
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