Scott's solution could be followed by
collapse y*, by(id)
Two more general comments:
1. Michael wants to go from a wide structure to another wide structure.
Thus that implies (at least) two -reshape-s, as Scott's code makes
clear.
The FAQ
FAQ . . . . . . . . . . . . . . . . . . . . . . . . Problems with
reshape
12/03 I am having problems with the reshape command. Can
you give further guidance?
http://www.stata.com/support/faqs/data/reshape3.html
has more examples of similar kind.
2. Although Michael can get what he wants, for most purposes the data
structure he asks for is, at least in Stata, much more awkward than the
equivalent long structure.
Nick
[email protected]
Scott Merryman
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?
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