Thanks Joseph. This is exactly what I wanted! :-)
Min
Quoting Joseph Coveney <[email protected]>:
> Min Zhang wrote:
>
> Nick, as for the first solution, can you give me more hint?
> I do not know how to set up the structure identifiers.
>
> > You can use -egen, seq()- to set up a
> > structure of identifiers. Recall that this
> > was an answer to one of your previous questions.
> >
> > Alternatively, if you want to mimic the structure
> > of the USA, just borrow a real dataset with
> > existing identifiers and then create your
> > "random counts" according to whatever precise
> > recipe you have in mind.
> >
> > Nick
> >
> > > I want to create a dataset which has a hierarchical linear structure.
> > > for example, a structure of states, counties:
> > >
> > > 50 states in total. For each state, create counties with
> > > random county counts.
> > > Then for each county, create school districts with random counts.
>
>
--------------------------------------------------------------------------------
>
> I'm not sure how to set up random counts of counties-within-states and
> districts-within-counties using -egen , seq()-, but perhaps the following
> might create the data structure that your'e looking for.
>
> (I'm not sure whether school districts are always nested within counties.
> In any event, I believe that you can get the actual rosters of counties and
> of school districts--Nick's second suggestion--from the U.S. Bureau of the
> Census. Check the bureau's website in the SAIPE area: "Small Area Income &
> Poverty Estimates--Model-based Estimates for States, Counties & School
> Districts.")
>
> Joseph Coveney
>
> set obs 50
> generate byte state_id = _n
> generate byte county_id = ceil(50 * uniform()) // 50 is arbitrary
> expand county_id
> bysort state_id: replace county_id = _n
> generate byte school_district_id = ceil(5 * uniform()) // 5 ditto
> expand school_district_id
> bysort state_id county_id: replace school_district_id = _n
>
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>
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