For -gllamm-, you actually provide the prefix rather than the full
name with the -weight- option. Hence, you should have as many weight
variables as you have levels (if your lowest level is the actual
response, rather than a variable in a latent variable system with many
dependent variables). Ideally, you should have the weights for all the
levels, but if you don't (most likely), define the level 1 weights as
the sampling weights from CPS, and all other weights, as 1:
gen wgt1 = <name of CPS weight variable>
gen wgt2 = 1
...
gllamm ... , ... weight( wgt )
For some models, it is the relative ratios of the weights that
matters. Some refs:
http://www.citeulike.org/user/ctacmo/article/850244,
http://www.citeulike.org/user/ctacmo/article/711637,
https://www.amstat.org/sections/srms/Proceedings/y2006/Files/JSM2006-000347.pdf
On 11/2/09, Doug Hess <[email protected]> wrote:
> I wish to use the weights provided in the Current Population Survey's
> supplements to analyze binary responses by individuals (and sometimes
> by households); I wish to use -gllamm- because the units are clustered
> in states and I wish to test the impact of policies that vary by
> states. However if I use the -weight(VAR)- command following the
> -gllamm- commands, it says the weight variables cannot be found.
>
> I guess I am naively using the -weight- command and the weight
> variables just as I would if the command was -iweight- when analyzing
> the data in -logit- without the clustering. Is this the wrong way to
> think of this? Any solutions? (The CPS weights are ten digits long
> including four decimal places).
>
> Thanks for any leads.
>
>
> Doug Hess
> PhD Candidate, Public Policy
> George Washington University
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--
Stas Kolenikov, also found at http://stas.kolenikov.name
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