Focus on any cohort, say the cohort that was grade 8 in 2011, grade 7
in 2010 and so forth. Evidently, the difference (year - grade) is
constant, and therefore an identifier, for that cohort. Thus after
gen id = year - grade
either
tsset id year
or
tsset id grade
defines a panel dataset with an identifier and a time variable and
time series operators can then be applied.
Nick
njcoxstata@gmail.com
On 29 April 2013 19:46, Stuart Buck <stuartbuck@gmail.com> wrote:
> Passage rates for all Texas schools for 2008, 2009, 2010, and 2011 --
> this is important -- by grade. So each row in the dataset is School,
> Year, Grade, and then scores (plus other demographic variables, etc.).
>
> In other words, the dataset looks like this:
>
> Year SchoolID Grade TestScore
> 2011 1 6 ***
> 2011 1 7 ***
> 2011 1 8 ***
>
> And so on and so forth -- multiple grades in each school in each year.
>
> Here's what I want:
>
> To be able to regress any given school's performance in Grade X in
> Year T on, among other things, how that same school did with the same
> cohort of kids in the previous grade (Grade X-1) in the previous year
> (Year T-1). I.e., if a middle school's Grade 8 passage rate in 2011 is
> the outcome, I'd like to be able to control for that same school's
> Grade 7 passage rate in 2010, thus giving a somewhat crude measure of
> how much that group of kids progressed since the previous year.
>
> How would I generate an all-purpose lagged TestScore variable for all
> the schools in the dataset, lagging by both year and grade at once?
> All the Stata instructional material I see on lagged variables just
> lags based on time, not on both time and some other variable too
> (grade).
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