Something like this?
clear
input id m81 m82 m85 a81 a82 a85
1 1.5 1.75 2 16 17 20
2 2.3 2.5 2.6 17 18 21
3 1.8 2 2.3 24 25 28
end
reshape long m a, i(id) j(year)
l
drop year
rename m y
reshape wide y , i(id ) j(a)
l
Scott
On Mon, Dec 8, 2008 at 7:25 AM, Michael Beets <[email protected]> wrote:
> Data transformation
>
>
>
> I have a wide formatted data set (each row is an individual measured
> over time) containing 15 measurements beginning at 1981 and ending at
> 2006 (example: m81, m82, m85, m86… m2006). At the initial year of
> measure (1981) the age range of individuals spanned 16 to 24yrs-old.
> The age of each individual at each measurement occasion is in 15 age
> variables (example: a81, a82, a85, a86… a2006).
>
>
>
> What I want to do is restructure the dataset so age (in years) is the
> variable with the measurement value listed for each individual.
>
>
>
> Here is an example of what I think this would look like:
>
>
>
> Current dataset:
>
> Id m81 m82 m85 a81 a82 a85
>
> 1 1.5 1.75 2 16
> 17 20
>
> 2 2.3 2.5 2.6 17
> 18 21
>
> 3 1.8 2 2.3 24
> 25 28
>
>
>
>
>
> Restructured dataset
>
> Id y16 y17 y18 …. Y20
> y21 y22 y23 y24 y25 …
> y28
>
> 1 1.5 1.75 2
>
> 2 2.3 2.5
> 2.6
>
> 3
> 1.8
> 2 2.3
>
>
>
> I've attempted to use "reshape" but this does not seem to give me the
> data structure I am after. I also attempted to write some code using
> "gen y16 = m81 if a81==16", but this cumbersome and subject to error.
> Is there an easier set of commands to restructure the data as
> indicated above?
>
> Thanks.
>
> *
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>
*
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