Re: st: ssm with hierarchical data

[Stas Kolenikov <skolenik@gmail.com>]

-ssm- is only a wrapper for the (far) more powerful -gllamm-. You need
to learn the latter... and you won't use -ssm- again :))

On Sat, Mar 20, 2010 at 3:24 PM, David Souther
<davidsoutheremail@gmail.com> wrote:
> I've got data on students across campuses with variables measured at
> both levels, and I would like to account for the different levels of
> aggregation while using -ssm-.  Currently, I'm using -ssm- to account
> for the switching for a certain student treatment (it's not selection
> because I observe students whether they got the treatment or not), so
> the model looks like:
>
> ssm count_truancies i_SES i_atrisk i_GPA  i_absences i_gender i_grade
> c_teacherexperience c_diversity c_crime year1 year2,  ///
> s(treatment =  i_SES i_atrisk i_GPA i_immigrant i_absences
> c_teacherexperience  c_treatmentFUNDS ) q(16) family(poiss) link(log)
> adapt
>
> Where the DV for the main equation is a count of the number of
> truancies, the switch model is determined by the dichotomous DV
> treatment, and there are several individual level vars (prefix of
> "i_") and campus level vars (prefix of "c_").  I've got another level
> of school district data that I'd like to add to this model at some
> point in the future.
>
> Is there some way to model the different levels of data aggregation
> (or some kind of hlm, xt, or clustering technique)??
>
> Thanks in advance,
> David
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-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
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