Dear statalisters,
I am trying to estimate a multilevel logit with this variables:
Dep var: hpoor (health conditions; 1 if bad)
Indep var: income quintiles (4 quintiles, highest quintile is the
reference category), age, age2, sex and finally a contextual variable
(named meanistr) measured at regional level (the id is reg) . My
purpose is to see if the socio-economic context has an influence on
the dep var. So I estimate the following, using gllamm command:
glamm hpoor quintpos1 quintpos2 quintpos3 quintpos4 age agesq age3
male meanistr, link (logit) fam (binom) nocons i (reg)
and I got the following:
number of level 1 units = 39777
number of level 2 units = 21
Condition Number = 1309484.3
gllamm model
log likelihood = -20815.479
------------------------------------------------------------------------------
hpoor | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
quintpos1 | .5610976 .0410717 13.66 0.000 .4805985 .6415968
quintpos2 | .4684868 .039587 11.83 0.000 .3908977 .5460759
quintpos3 | .4766715 .038078 12.52 0.000 .40204 .551303
quintpos4 | .2694107 .0372995 7.22 0.000 .196305 .3425163
age | .1018888 .0121446 8.39 0.000 .0780858 .1256917
agesq | -.000771 .0002509 -3.07 0.002 -.0012627 -.0002792
age3 | 6.21e-06 1.69e-06 3.67 0.000 2.90e-06 9.52e-06
male | -.0921198 .025821 -3.57 0.000 -.142728 -.0415115
meanistr | -1.977139 .08596 -23.00 0.000 -2.145617 -1.80866
------------------------------------------------------------------------------
Variances and covariances of random effects
------------------------------------------------------------------------------
***level 2 (reg)
var(1): .02703922 (.00502425)
------------------------------------------------------------------------------
My questions are:
1) is right gllamm command for my research purpose (asses the context
role)? or is it better an xtlogit?
2) why I get just 2-level variance? In this way I am not able to
mesaure the percentage of total variance explained by 2-level variance
(that is the role of context)
3) If I use already a variable mesaured at regional level to asses the
role of context, Would I need to use a multi-level model or I could
just use a cluster option to take off the correlation intra-region?
I appreciate any hint.
Many thanks in advance
Vincenzo
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