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Re: st: Hierarchical model


From   Evans Jadotte <evans.jadotte@uab.es>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Hierarchical model
Date   Sat, 03 Oct 2009 16:53:11 +0200

Maarten buis wrote:
--- On Sat, 3/10/09, Evans Jadotte <evans.jadotte@uab.es> wrote:
.xi: quietly xtmixed logequiv i.education i.mpsex
mpage* i.sector non_farm
small_cattle large_cattle s_s_cattle shock_cattle dumland1
tech_land
electricity landline piped_water road_access death d_rem
i.hhtype
||cluster:, var

estimates store model1

.xi: quietly xtmixed logequiv i.education i.mpsex mpage*
i.sector non_farm
small_cattle large_cattle s_s_cattle shock_cattle dumland1
tech_land
electricity landline piped_water road_access death d_rem
i.hhtype ||strata:
||cluster:, var

. estimates store model2 . lrtest model1 model2
This test is a test of a null hypothesis on the edge of the parameter space (the strata level variance is >= 0, so 0 is on the edge of allowable values for that variance). Things get weird when you perform such a test, so be careful.
For more on this see: -help j_chibar-.
The last test strongly suggests that cluster is nested into
strata and that the latter should be in the model. I tried estimating the other way around (strata nested into cluster) just to check, and convergence failed. So, based on the
three-level model:

It appears you are trying to empirically determine the nesting
structure in your data. You should not need to do this as it
should be a-priori clear from the design of your study. If the
nesting is not strictly fixed by design you are probably dealing with a crossed random effects model. In any case the
nesting structure is determined by the design of your study and
is not an empirical question.
Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------


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Hi Maarten,

Thanks for your input. I must say in advance that I am relatively new in Stata and my knowledge is very limited, so any help would be much appreciated.

I tried the estimation (cluster nested into strata) just to validate the results from estimating cluster nested into strata. The nesting is strictly fixed by design so I believe it is not a crossed random effects model. To be more specific, "clusters" are in my study "villages or communities" while "strata" are "administrative regions", each of which includes various communities (something similar to a Länder in Germany). I understand now that the H0 for this lrtest implies:

Var(strata) = Cov(strata, cluster) = 0

In my model, I need Cov(strata, cluster) = 0, while Var(strata) > 0.

If one of the conditions of the H0 fails (in this case Var(strata) ≠ 0), what would be the procedure to follow? In fact, the result I am looking for Var(strata) > 0 and Cov(strata, cluster) = 0 is what I got.

Thanks,

Evans
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